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Tuần 1 - Ngày 10 tháng 7 năm 2019
- Giới thiệu về khóa học
- Hướng dẫn viết chương trình Python trên web
- Hướng dẫn sử dụng PyCharm
- Tổng quan về Python
- Kỹ năng sử dụng Google search
- Viết tài liệu kỹ thuật dùng Markdown
- Hàm xây dựng sẵn trong Python – math và random
- Cài đặt các công thức toán cơ bản
- Xây dựng hàm trong python
- Điều kiện if-else
- Những lỗi thường gặp trong Python
- Reading assignment
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Tuần 2 - Ngày 17 tháng 7 năm 2019
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Tuần 3 - Ngày 24 tháng 7 năm 2019
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Tuần 4 - Ngày 31 tháng 7 năm 2019
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Tuần 5 - Ngày 7 tháng 8 năm 2019
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Advanced Python
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Tuần 6 - Ngày 14 tháng 8 năm 2019
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Tuần 7 - Ngày 28 tháng 8 năm 2019
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Tuần 8
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Tuần 9
Vectorization
Trong bài này, chúng ta sẽ cài đặt bài toán dự đoán giá nhà dùng linear regression bằng hai cách: cài đặt dùng chỉ mục index và dùng những hàm trong numpy đã hỗ trợ kỹ thuật vectorization. Sau đó, chúng ta sẽ quan sát tốc độ của hai loại cài đặt.
1. Dự đoán giá nhà theo diện tích
Chúng ta sẽ sử dụng dữ liệu dự đoán giá nhà theo diện tích nhà, được hiển thị ở bảng sau
3.87 | 5.38 |
---|---|
2.29 | 3.45 |
5.17 | 6.94 |
4.93 | 7.1 |
4 | 5.47 |
3.97 | 5.31 |
6.77 | 8.89 |
2.48 | 4.08 |
2.85 | 4.59 |
6.43 | 8.52 |
6.99 | 8.63 |
2.74 | 4.29 |
2.07 | 3.34 |
3.64 | 5.48 |
5.66 | 7.4 |
1.85 | 3.3 |
4.73 | 6.19 |
4.55 | 6.46 |
6.4 | 8.65 |
2.14 | 3.35 |
Code để đọc và xử lý data
import numpy as np from numpy import genfromtxt import matplotlib.pyplot as plt data = genfromtxt('my_house_price_prediction.csv', delimiter=',') m = data.shape[0] n = data.shape[1] x = data[:,0] y = data[:,1] X = np.c_[np.ones((m, 1)), x] plt.scatter(x, y) plt.xlabel('Diện tích nhà (x 100$m^2$)') plt.ylabel('Giá nhà (chục lượng vàng)') plt.show()
Cài theo cách dùng chỉ mục index
# No Vectorization - batch gradien descent theta = np.random.randn(n) # loss function def loss_function(theta = theta, x=X, y=y, m=m, n=n): loss = 0 for i in range(m): hypo_i = 0 for j in range(n): hypo_i += theta[j]*X[i,j] loss_i = (hypo_i - y[i])**2 loss += loss_i loss = (1/m)*loss return loss # training learning_rate = 0.01 theta = np.ones(n) loss_list = [] epoches = 50 for itr in range(epoches): dev_list = [] for k in range(n): dev_sum = 0 for i in range(m): ## Feed forward hypo_i = 0 for j in range(n): hypo_i += theta[j]*X[i,j] # derivative dev_i = (hypo_i - y[i])*X[i,k] dev_sum += dev_i dev_sum = (2/m)*dev_sum dev_list.append(dev_sum) theta = theta - learning_rate*np.array(dev_list) loss_val = loss_function(theta) loss_list.append(loss_val) plt.plot(np.arange(0, epoches),loss_list) plt.xlabel('epoch') plt.ylabel('Giá trị loss')
Giá trị loss qua các vòng lặp
Cài theo phương pháp vectorization
# Vectorization # Initialize theta theta = np.random.randn(n) def cost(theta, X=X, y=y, m=m): cost = np.dot(np.dot(X,theta) - y, np.dot(X,theta) - y) cost = (1/m)*cost return cost # learning rate learning_rate = 0.01 cost_list = [] epoches = 500 for i in range(epoches): output = np.dot(X,theta) loss_grd = output - y gradients = (2/m)*np.dot(np.transpose(X), loss_grd) theta = theta - learning_rate*gradients cost_val = cost(theta) cost_list.append(cost_val) plt.plot(np.arange(0, epoches),cost_list) plt.xlabel('epoch') plt.ylabel('Giá trị loss')
Giá trị loss qua các vòng lặp
2. Dự đoán giá nhà Boston
Dữ liệu nhà Boston được mô tả ở bảng sau
crim | zn | indus | chas | nox | rm | age | dis | rad | tax | ptratio | black | lstat | medv |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.00632 | 18 | 2.31 | 0 | 0.538 | 6.575 | 65.2 | 4.09 | 1 | 296 | 15.3 | 396.9 | 4.98 | 24 |
0.02731 | 0 | 7.07 | 0 | 0.469 | 6.421 | 78.9 | 4.9671 | 2 | 242 | 17.8 | 396.9 | 9.14 | 21.6 |
0.03237 | 0 | 2.18 | 0 | 0.458 | 6.998 | 45.8 | 6.0622 | 3 | 222 | 18.7 | 394.63 | 2.94 | 33.4 |
0.06905 | 0 | 2.18 | 0 | 0.458 | 7.147 | 54.2 | 6.0622 | 3 | 222 | 18.7 | 396.9 | 5.33 | 36.2 |
0.08829 | 12.5 | 7.87 | 0 | 0.524 | 6.012 | 66.6 | 5.5605 | 5 | 311 | 15.2 | 395.6 | 12.43 | 22.9 |
0.22489 | 12.5 | 7.87 | 0 | 0.524 | 6.377 | 94.3 | 6.3467 | 5 | 311 | 15.2 | 392.52 | 20.45 | 15 |
0.11747 | 12.5 | 7.87 | 0 | 0.524 | 6.009 | 82.9 | 6.2267 | 5 | 311 | 15.2 | 396.9 | 13.27 | 18.9 |
0.09378 | 12.5 | 7.87 | 0 | 0.524 | 5.889 | 39 | 5.4509 | 5 | 311 | 15.2 | 390.5 | 15.71 | 21.7 |
0.62976 | 0 | 8.14 | 0 | 0.538 | 5.949 | 61.8 | 4.7075 | 4 | 307 | 21 | 396.9 | 8.26 | 20.4 |
0.63796 | 0 | 8.14 | 0 | 0.538 | 6.096 | 84.5 | 4.4619 | 4 | 307 | 21 | 380.02 | 10.26 | 18.2 |
0.62739 | 0 | 8.14 | 0 | 0.538 | 5.834 | 56.5 | 4.4986 | 4 | 307 | 21 | 395.62 | 8.47 | 19.9 |
1.05393 | 0 | 8.14 | 0 | 0.538 | 5.935 | 29.3 | 4.4986 | 4 | 307 | 21 | 386.85 | 6.58 | 23.1 |
0.80271 | 0 | 8.14 | 0 | 0.538 | 5.456 | 36.6 | 3.7965 | 4 | 307 | 21 | 288.99 | 11.69 | 20.2 |
1.25179 | 0 | 8.14 | 0 | 0.538 | 5.57 | 98.1 | 3.7979 | 4 | 307 | 21 | 376.57 | 21.02 | 13.6 |
0.85204 | 0 | 8.14 | 0 | 0.538 | 5.965 | 89.2 | 4.0123 | 4 | 307 | 21 | 392.53 | 13.83 | 19.6 |
1.23247 | 0 | 8.14 | 0 | 0.538 | 6.142 | 91.7 | 3.9769 | 4 | 307 | 21 | 396.9 | 18.72 | 15.2 |
0.98843 | 0 | 8.14 | 0 | 0.538 | 5.813 | 100 | 4.0952 | 4 | 307 | 21 | 394.54 | 19.88 | 14.5 |
0.95577 | 0 | 8.14 | 0 | 0.538 | 6.047 | 88.8 | 4.4534 | 4 | 307 | 21 | 306.38 | 17.28 | 14.8 |
1.13081 | 0 | 8.14 | 0 | 0.538 | 5.713 | 94.1 | 4.233 | 4 | 307 | 21 | 360.17 | 22.6 | 12.7 |
1.35472 | 0 | 8.14 | 0 | 0.538 | 6.072 | 100 | 4.175 | 4 | 307 | 21 | 376.73 | 13.04 | 14.5 |
1.61282 | 0 | 8.14 | 0 | 0.538 | 6.096 | 96.9 | 3.7598 | 4 | 307 | 21 | 248.31 | 20.34 | 13.5 |
0.17505 | 0 | 5.96 | 0 | 0.499 | 5.966 | 30.2 | 3.8473 | 5 | 279 | 19.2 | 393.43 | 10.13 | 24.7 |
0.02763 | 75 | 2.95 | 0 | 0.428 | 6.595 | 21.8 | 5.4011 | 3 | 252 | 18.3 | 395.63 | 4.32 | 30.8 |
0.03359 | 75 | 2.95 | 0 | 0.428 | 7.024 | 15.8 | 5.4011 | 3 | 252 | 18.3 | 395.62 | 1.98 | 34.9 |
0.1415 | 0 | 6.91 | 0 | 0.448 | 6.169 | 6.6 | 5.7209 | 3 | 233 | 17.9 | 383.37 | 5.81 | 25.3 |
0.15936 | 0 | 6.91 | 0 | 0.448 | 6.211 | 6.5 | 5.7209 | 3 | 233 | 17.9 | 394.46 | 7.44 | 24.7 |
0.12269 | 0 | 6.91 | 0 | 0.448 | 6.069 | 40 | 5.7209 | 3 | 233 | 17.9 | 389.39 | 9.55 | 21.2 |
0.17142 | 0 | 6.91 | 0 | 0.448 | 5.682 | 33.8 | 5.1004 | 3 | 233 | 17.9 | 396.9 | 10.21 | 19.3 |
0.18836 | 0 | 6.91 | 0 | 0.448 | 5.786 | 33.3 | 5.1004 | 3 | 233 | 17.9 | 396.9 | 14.15 | 20 |
0.22927 | 0 | 6.91 | 0 | 0.448 | 6.03 | 85.5 | 5.6894 | 3 | 233 | 17.9 | 392.74 | 18.8 | 16.6 |
0.21977 | 0 | 6.91 | 0 | 0.448 | 5.602 | 62 | 6.0877 | 3 | 233 | 17.9 | 396.9 | 16.2 | 19.4 |
0.08873 | 21 | 5.64 | 0 | 0.439 | 5.963 | 45.7 | 6.8147 | 4 | 243 | 16.8 | 395.56 | 13.45 | 19.7 |
0.04337 | 21 | 5.64 | 0 | 0.439 | 6.115 | 63 | 6.8147 | 4 | 243 | 16.8 | 393.97 | 9.43 | 20.5 |
0.04981 | 21 | 5.64 | 0 | 0.439 | 5.998 | 21.4 | 6.8147 | 4 | 243 | 16.8 | 396.9 | 8.43 | 23.4 |
0.0136 | 75 | 4 | 0 | 0.41 | 5.888 | 47.6 | 7.3197 | 3 | 469 | 21.1 | 396.9 | 14.8 | 18.9 |
0.01311 | 90 | 1.22 | 0 | 0.403 | 7.249 | 21.9 | 8.6966 | 5 | 226 | 17.9 | 395.93 | 4.81 | 35.4 |
0.02055 | 85 | 0.74 | 0 | 0.41 | 6.383 | 35.7 | 9.1876 | 2 | 313 | 17.3 | 396.9 | 5.77 | 24.7 |
0.01432 | 100 | 1.32 | 0 | 0.411 | 6.816 | 40.5 | 8.3248 | 5 | 256 | 15.1 | 392.9 | 3.95 | 31.6 |
0.15445 | 25 | 5.13 | 0 | 0.453 | 6.145 | 29.2 | 7.8148 | 8 | 284 | 19.7 | 390.68 | 6.86 | 23.3 |
0.14932 | 25 | 5.13 | 0 | 0.453 | 5.741 | 66.2 | 7.2254 | 8 | 284 | 19.7 | 395.11 | 13.15 | 18.7 |
0.17171 | 25 | 5.13 | 0 | 0.453 | 5.966 | 93.4 | 6.8185 | 8 | 284 | 19.7 | 378.08 | 14.44 | 16 |
0.1265 | 25 | 5.13 | 0 | 0.453 | 6.762 | 43.4 | 7.9809 | 8 | 284 | 19.7 | 395.58 | 9.5 | 25 |
0.01951 | 17.5 | 1.38 | 0 | 0.4161 | 7.104 | 59.5 | 9.2229 | 3 | 216 | 18.6 | 393.24 | 8.05 | 33 |
0.03584 | 80 | 3.37 | 0 | 0.398 | 6.29 | 17.8 | 6.6115 | 4 | 337 | 16.1 | 396.9 | 4.67 | 23.5 |
0.04379 | 80 | 3.37 | 0 | 0.398 | 5.787 | 31.1 | 6.6115 | 4 | 337 | 16.1 | 396.9 | 10.24 | 19.4 |
0.05789 | 12.5 | 6.07 | 0 | 0.409 | 5.878 | 21.4 | 6.498 | 4 | 345 | 18.9 | 396.21 | 8.1 | 22 |
0.13554 | 12.5 | 6.07 | 0 | 0.409 | 5.594 | 36.8 | 6.498 | 4 | 345 | 18.9 | 396.9 | 13.09 | 17.4 |
0.08826 | 0 | 10.81 | 0 | 0.413 | 6.417 | 6.6 | 5.2873 | 4 | 305 | 19.2 | 383.73 | 6.72 | 24.2 |
0.09164 | 0 | 10.81 | 0 | 0.413 | 6.065 | 7.8 | 5.2873 | 4 | 305 | 19.2 | 390.91 | 5.52 | 22.8 |
0.19539 | 0 | 10.81 | 0 | 0.413 | 6.245 | 6.2 | 5.2873 | 4 | 305 | 19.2 | 377.17 | 7.54 | 23.4 |
0.07896 | 0 | 12.83 | 0 | 0.437 | 6.273 | 6 | 4.2515 | 5 | 398 | 18.7 | 394.92 | 6.78 | 24.1 |
0.09512 | 0 | 12.83 | 0 | 0.437 | 6.286 | 45 | 4.5026 | 5 | 398 | 18.7 | 383.23 | 8.94 | 21.4 |
0.10153 | 0 | 12.83 | 0 | 0.437 | 6.279 | 74.5 | 4.0522 | 5 | 398 | 18.7 | 373.66 | 11.97 | 20 |
0.08707 | 0 | 12.83 | 0 | 0.437 | 6.14 | 45.8 | 4.0905 | 5 | 398 | 18.7 | 386.96 | 10.27 | 20.8 |
0.04113 | 25 | 4.86 | 0 | 0.426 | 6.727 | 33.5 | 5.4007 | 4 | 281 | 19 | 396.9 | 5.29 | 28 |
0.04462 | 25 | 4.86 | 0 | 0.426 | 6.619 | 70.4 | 5.4007 | 4 | 281 | 19 | 395.63 | 7.22 | 23.9 |
0.03551 | 25 | 4.86 | 0 | 0.426 | 6.167 | 46.7 | 5.4007 | 4 | 281 | 19 | 390.64 | 7.51 | 22.9 |
0.05059 | 0 | 4.49 | 0 | 0.449 | 6.389 | 48 | 4.7794 | 3 | 247 | 18.5 | 396.9 | 9.62 | 23.9 |
0.05735 | 0 | 4.49 | 0 | 0.449 | 6.63 | 56.1 | 4.4377 | 3 | 247 | 18.5 | 392.3 | 6.53 | 26.6 |
0.05188 | 0 | 4.49 | 0 | 0.449 | 6.015 | 45.1 | 4.4272 | 3 | 247 | 18.5 | 395.99 | 12.86 | 22.5 |
0.07151 | 0 | 4.49 | 0 | 0.449 | 6.121 | 56.8 | 3.7476 | 3 | 247 | 18.5 | 395.15 | 8.44 | 22.2 |
0.0566 | 0 | 3.41 | 0 | 0.489 | 7.007 | 86.3 | 3.4217 | 2 | 270 | 17.8 | 396.9 | 5.5 | 23.6 |
0.05302 | 0 | 3.41 | 0 | 0.489 | 7.079 | 63.1 | 3.4145 | 2 | 270 | 17.8 | 396.06 | 5.7 | 28.7 |
0.04684 | 0 | 3.41 | 0 | 0.489 | 6.417 | 66.1 | 3.0923 | 2 | 270 | 17.8 | 392.18 | 8.81 | 22.6 |
0.02875 | 28 | 15.04 | 0 | 0.464 | 6.211 | 28.9 | 3.6659 | 4 | 270 | 18.2 | 396.33 | 6.21 | 25 |
0.04294 | 28 | 15.04 | 0 | 0.464 | 6.249 | 77.3 | 3.615 | 4 | 270 | 18.2 | 396.9 | 10.59 | 20.6 |
0.11504 | 0 | 2.89 | 0 | 0.445 | 6.163 | 69.6 | 3.4952 | 2 | 276 | 18 | 391.83 | 11.34 | 21.4 |
0.14866 | 0 | 8.56 | 0 | 0.52 | 6.727 | 79.9 | 2.7778 | 5 | 384 | 20.9 | 394.76 | 9.42 | 27.5 |
0.11432 | 0 | 8.56 | 0 | 0.52 | 6.781 | 71.3 | 2.8561 | 5 | 384 | 20.9 | 395.58 | 7.67 | 26.5 |
0.22876 | 0 | 8.56 | 0 | 0.52 | 6.405 | 85.4 | 2.7147 | 5 | 384 | 20.9 | 70.8 | 10.63 | 18.6 |
0.21161 | 0 | 8.56 | 0 | 0.52 | 6.137 | 87.4 | 2.7147 | 5 | 384 | 20.9 | 394.47 | 13.44 | 19.3 |
0.1712 | 0 | 8.56 | 0 | 0.52 | 5.836 | 91.9 | 2.211 | 5 | 384 | 20.9 | 395.67 | 18.66 | 19.5 |
0.13117 | 0 | 8.56 | 0 | 0.52 | 6.127 | 85.2 | 2.1224 | 5 | 384 | 20.9 | 387.69 | 14.09 | 20.4 |
0.12802 | 0 | 8.56 | 0 | 0.52 | 6.474 | 97.1 | 2.4329 | 5 | 384 | 20.9 | 395.24 | 12.27 | 19.8 |
0.26363 | 0 | 8.56 | 0 | 0.52 | 6.229 | 91.2 | 2.5451 | 5 | 384 | 20.9 | 391.23 | 15.55 | 19.4 |
0.10084 | 0 | 10.01 | 0 | 0.547 | 6.715 | 81.6 | 2.6775 | 6 | 432 | 17.8 | 395.59 | 10.16 | 22.8 |
0.14231 | 0 | 10.01 | 0 | 0.547 | 6.254 | 84.2 | 2.2565 | 6 | 432 | 17.8 | 388.74 | 10.45 | 18.5 |
0.13158 | 0 | 10.01 | 0 | 0.547 | 6.176 | 72.5 | 2.7301 | 6 | 432 | 17.8 | 393.3 | 12.04 | 21.2 |
0.15098 | 0 | 10.01 | 0 | 0.547 | 6.021 | 82.6 | 2.7474 | 6 | 432 | 17.8 | 394.51 | 10.3 | 19.2 |
0.13058 | 0 | 10.01 | 0 | 0.547 | 5.872 | 73.1 | 2.4775 | 6 | 432 | 17.8 | 338.63 | 15.37 | 20.4 |
0.14476 | 0 | 10.01 | 0 | 0.547 | 5.731 | 65.2 | 2.7592 | 6 | 432 | 17.8 | 391.5 | 13.61 | 19.3 |
0.06899 | 0 | 25.65 | 0 | 0.581 | 5.87 | 69.7 | 2.2577 | 2 | 188 | 19.1 | 389.15 | 14.37 | 22 |
0.07165 | 0 | 25.65 | 0 | 0.581 | 6.004 | 84.1 | 2.1974 | 2 | 188 | 19.1 | 377.67 | 14.27 | 20.3 |
0.09299 | 0 | 25.65 | 0 | 0.581 | 5.961 | 92.9 | 2.0869 | 2 | 188 | 19.1 | 378.09 | 17.93 | 20.5 |
0.15038 | 0 | 25.65 | 0 | 0.581 | 5.856 | 97 | 1.9444 | 2 | 188 | 19.1 | 370.31 | 25.41 | 17.3 |
0.09849 | 0 | 25.65 | 0 | 0.581 | 5.879 | 95.8 | 2.0063 | 2 | 188 | 19.1 | 379.38 | 17.58 | 18.8 |
0.38735 | 0 | 25.65 | 0 | 0.581 | 5.613 | 95.6 | 1.7572 | 2 | 188 | 19.1 | 359.29 | 27.26 | 15.7 |
0.25915 | 0 | 21.89 | 0 | 0.624 | 5.693 | 96 | 1.7883 | 4 | 437 | 21.2 | 392.11 | 17.19 | 16.2 |
0.32543 | 0 | 21.89 | 0 | 0.624 | 6.431 | 98.8 | 1.8125 | 4 | 437 | 21.2 | 396.9 | 15.39 | 18 |
1.19294 | 0 | 21.89 | 0 | 0.624 | 6.326 | 97.7 | 2.271 | 4 | 437 | 21.2 | 396.9 | 12.26 | 19.6 |
0.32982 | 0 | 21.89 | 0 | 0.624 | 5.822 | 95.4 | 2.4699 | 4 | 437 | 21.2 | 388.69 | 15.03 | 18.4 |
0.97617 | 0 | 21.89 | 0 | 0.624 | 5.757 | 98.4 | 2.346 | 4 | 437 | 21.2 | 262.76 | 17.31 | 15.6 |
0.32264 | 0 | 21.89 | 0 | 0.624 | 5.942 | 93.5 | 1.9669 | 4 | 437 | 21.2 | 378.25 | 16.9 | 17.4 |
0.35233 | 0 | 21.89 | 0 | 0.624 | 6.454 | 98.4 | 1.8498 | 4 | 437 | 21.2 | 394.08 | 14.59 | 17.1 |
0.2498 | 0 | 21.89 | 0 | 0.624 | 5.857 | 98.2 | 1.6686 | 4 | 437 | 21.2 | 392.04 | 21.32 | 13.3 |
0.54452 | 0 | 21.89 | 0 | 0.624 | 6.151 | 97.9 | 1.6687 | 4 | 437 | 21.2 | 396.9 | 18.46 | 17.8 |
1.62864 | 0 | 21.89 | 0 | 0.624 | 5.019 | 100 | 1.4394 | 4 | 437 | 21.2 | 396.9 | 34.41 | 14.4 |
3.32105 | 0 | 19.58 | 1 | 0.871 | 5.403 | 100 | 1.3216 | 5 | 403 | 14.7 | 396.9 | 26.82 | 13.4 |
2.37934 | 0 | 19.58 | 0 | 0.871 | 6.13 | 100 | 1.4191 | 5 | 403 | 14.7 | 172.91 | 27.8 | 13.8 |
2.36862 | 0 | 19.58 | 0 | 0.871 | 4.926 | 95.7 | 1.4608 | 5 | 403 | 14.7 | 391.71 | 29.53 | 14.6 |
2.33099 | 0 | 19.58 | 0 | 0.871 | 5.186 | 93.8 | 1.5296 | 5 | 403 | 14.7 | 356.99 | 28.32 | 17.8 |
2.73397 | 0 | 19.58 | 0 | 0.871 | 5.597 | 94.9 | 1.5257 | 5 | 403 | 14.7 | 351.85 | 21.45 | 15.4 |
1.6566 | 0 | 19.58 | 0 | 0.871 | 6.122 | 97.3 | 1.618 | 5 | 403 | 14.7 | 372.8 | 14.1 | 21.5 |
2.14918 | 0 | 19.58 | 0 | 0.871 | 5.709 | 98.5 | 1.6232 | 5 | 403 | 14.7 | 261.95 | 15.79 | 19.4 |
1.41385 | 0 | 19.58 | 1 | 0.871 | 6.129 | 96 | 1.7494 | 5 | 403 | 14.7 | 321.02 | 15.12 | 17 |
2.44668 | 0 | 19.58 | 0 | 0.871 | 5.272 | 94 | 1.7364 | 5 | 403 | 14.7 | 88.63 | 16.14 | 13.1 |
1.34284 | 0 | 19.58 | 0 | 0.605 | 6.066 | 100 | 1.7573 | 5 | 403 | 14.7 | 353.89 | 6.43 | 24.3 |
1.42502 | 0 | 19.58 | 0 | 0.871 | 6.51 | 100 | 1.7659 | 5 | 403 | 14.7 | 364.31 | 7.39 | 23.3 |
1.27346 | 0 | 19.58 | 1 | 0.605 | 6.25 | 92.6 | 1.7984 | 5 | 403 | 14.7 | 338.92 | 5.5 | 27 |
1.46336 | 0 | 19.58 | 0 | 0.605 | 7.489 | 90.8 | 1.9709 | 5 | 403 | 14.7 | 374.43 | 1.73 | 50 |
1.51902 | 0 | 19.58 | 1 | 0.605 | 8.375 | 93.9 | 2.162 | 5 | 403 | 14.7 | 388.45 | 3.32 | 50 |
2.24236 | 0 | 19.58 | 0 | 0.605 | 5.854 | 91.8 | 2.422 | 5 | 403 | 14.7 | 395.11 | 11.64 | 22.7 |
2.924 | 0 | 19.58 | 0 | 0.605 | 6.101 | 93 | 2.2834 | 5 | 403 | 14.7 | 240.16 | 9.81 | 25 |
2.01019 | 0 | 19.58 | 0 | 0.605 | 7.929 | 96.2 | 2.0459 | 5 | 403 | 14.7 | 369.3 | 3.7 | 50 |
1.80028 | 0 | 19.58 | 0 | 0.605 | 5.877 | 79.2 | 2.4259 | 5 | 403 | 14.7 | 227.61 | 12.14 | 23.8 |
2.44953 | 0 | 19.58 | 0 | 0.605 | 6.402 | 95.2 | 2.2625 | 5 | 403 | 14.7 | 330.04 | 11.32 | 22.3 |
1.20742 | 0 | 19.58 | 0 | 0.605 | 5.875 | 94.6 | 2.4259 | 5 | 403 | 14.7 | 292.29 | 14.43 | 17.4 |
2.3139 | 0 | 19.58 | 0 | 0.605 | 5.88 | 97.3 | 2.3887 | 5 | 403 | 14.7 | 348.13 | 12.03 | 19.1 |
0.13914 | 0 | 4.05 | 0 | 0.51 | 5.572 | 88.5 | 2.5961 | 5 | 296 | 16.6 | 396.9 | 14.69 | 23.1 |
0.09178 | 0 | 4.05 | 0 | 0.51 | 6.416 | 84.1 | 2.6463 | 5 | 296 | 16.6 | 395.5 | 9.04 | 23.6 |
0.08447 | 0 | 4.05 | 0 | 0.51 | 5.859 | 68.7 | 2.7019 | 5 | 296 | 16.6 | 393.23 | 9.64 | 22.6 |
0.06664 | 0 | 4.05 | 0 | 0.51 | 6.546 | 33.1 | 3.1323 | 5 | 296 | 16.6 | 390.96 | 5.33 | 29.4 |
0.07022 | 0 | 4.05 | 0 | 0.51 | 6.02 | 47.2 | 3.5549 | 5 | 296 | 16.6 | 393.23 | 10.11 | 23.2 |
0.05425 | 0 | 4.05 | 0 | 0.51 | 6.315 | 73.4 | 3.3175 | 5 | 296 | 16.6 | 395.6 | 6.29 | 24.6 |
0.06642 | 0 | 4.05 | 0 | 0.51 | 6.86 | 74.4 | 2.9153 | 5 | 296 | 16.6 | 391.27 | 6.92 | 29.9 |
0.0578 | 0 | 2.46 | 0 | 0.488 | 6.98 | 58.4 | 2.829 | 3 | 193 | 17.8 | 396.9 | 5.04 | 37.2 |
0.06588 | 0 | 2.46 | 0 | 0.488 | 7.765 | 83.3 | 2.741 | 3 | 193 | 17.8 | 395.56 | 7.56 | 39.8 |
0.06888 | 0 | 2.46 | 0 | 0.488 | 6.144 | 62.2 | 2.5979 | 3 | 193 | 17.8 | 396.9 | 9.45 | 36.2 |
0.09103 | 0 | 2.46 | 0 | 0.488 | 7.155 | 92.2 | 2.7006 | 3 | 193 | 17.8 | 394.12 | 4.82 | 37.9 |
0.10008 | 0 | 2.46 | 0 | 0.488 | 6.563 | 95.6 | 2.847 | 3 | 193 | 17.8 | 396.9 | 5.68 | 32.5 |
0.05602 | 0 | 2.46 | 0 | 0.488 | 7.831 | 53.6 | 3.1992 | 3 | 193 | 17.8 | 392.63 | 4.45 | 50 |
0.07875 | 45 | 3.44 | 0 | 0.437 | 6.782 | 41.1 | 3.7886 | 5 | 398 | 15.2 | 393.87 | 6.68 | 32 |
0.0837 | 45 | 3.44 | 0 | 0.437 | 7.185 | 38.9 | 4.5667 | 5 | 398 | 15.2 | 396.9 | 5.39 | 34.9 |
0.09068 | 45 | 3.44 | 0 | 0.437 | 6.951 | 21.5 | 6.4798 | 5 | 398 | 15.2 | 377.68 | 5.1 | 37 |
0.06911 | 45 | 3.44 | 0 | 0.437 | 6.739 | 30.8 | 6.4798 | 5 | 398 | 15.2 | 389.71 | 4.69 | 30.5 |
0.08664 | 45 | 3.44 | 0 | 0.437 | 7.178 | 26.3 | 6.4798 | 5 | 398 | 15.2 | 390.49 | 2.87 | 36.4 |
0.02187 | 60 | 2.93 | 0 | 0.401 | 6.8 | 9.9 | 6.2196 | 1 | 265 | 15.6 | 393.37 | 5.03 | 31.1 |
0.01439 | 60 | 2.93 | 0 | 0.401 | 6.604 | 18.8 | 6.2196 | 1 | 265 | 15.6 | 376.7 | 4.38 | 29.1 |
0.04666 | 80 | 1.52 | 0 | 0.404 | 7.107 | 36.6 | 7.309 | 2 | 329 | 12.6 | 354.31 | 8.61 | 30.3 |
0.01778 | 95 | 1.47 | 0 | 0.403 | 7.135 | 13.9 | 7.6534 | 3 | 402 | 17 | 384.3 | 4.45 | 32.9 |
0.03445 | 82.5 | 2.03 | 0 | 0.415 | 6.162 | 38.4 | 6.27 | 2 | 348 | 14.7 | 393.77 | 7.43 | 24.1 |
0.0351 | 95 | 2.68 | 0 | 0.4161 | 7.853 | 33.2 | 5.118 | 4 | 224 | 14.7 | 392.78 | 3.81 | 48.5 |
0.02009 | 95 | 2.68 | 0 | 0.4161 | 8.034 | 31.9 | 5.118 | 4 | 224 | 14.7 | 390.55 | 2.88 | 50 |
0.13642 | 0 | 10.59 | 0 | 0.489 | 5.891 | 22.3 | 3.9454 | 4 | 277 | 18.6 | 396.9 | 10.87 | 22.6 |
0.22969 | 0 | 10.59 | 0 | 0.489 | 6.326 | 52.5 | 4.3549 | 4 | 277 | 18.6 | 394.87 | 10.97 | 24.4 |
0.13587 | 0 | 10.59 | 1 | 0.489 | 6.064 | 59.1 | 4.2392 | 4 | 277 | 18.6 | 381.32 | 14.66 | 24.4 |
0.37578 | 0 | 10.59 | 1 | 0.489 | 5.404 | 88.6 | 3.665 | 4 | 277 | 18.6 | 395.24 | 23.98 | 19.3 |
0.14052 | 0 | 10.59 | 0 | 0.489 | 6.375 | 32.3 | 3.9454 | 4 | 277 | 18.6 | 385.81 | 9.38 | 28.1 |
0.28955 | 0 | 10.59 | 0 | 0.489 | 5.412 | 9.8 | 3.5875 | 4 | 277 | 18.6 | 348.93 | 29.55 | 23.7 |
0.0456 | 0 | 13.89 | 1 | 0.55 | 5.888 | 56 | 3.1121 | 5 | 276 | 16.4 | 392.8 | 13.51 | 23.3 |
0.40771 | 0 | 6.2 | 1 | 0.507 | 6.164 | 91.3 | 3.048 | 8 | 307 | 17.4 | 395.24 | 21.46 | 21.7 |
0.62356 | 0 | 6.2 | 1 | 0.507 | 6.879 | 77.7 | 3.2721 | 8 | 307 | 17.4 | 390.39 | 9.93 | 27.5 |
0.6147 | 0 | 6.2 | 0 | 0.507 | 6.618 | 80.8 | 3.2721 | 8 | 307 | 17.4 | 396.9 | 7.6 | 30.1 |
0.31533 | 0 | 6.2 | 0 | 0.504 | 8.266 | 78.3 | 2.8944 | 8 | 307 | 17.4 | 385.05 | 4.14 | 44.8 |
0.52693 | 0 | 6.2 | 0 | 0.504 | 8.725 | 83 | 2.8944 | 8 | 307 | 17.4 | 382 | 4.63 | 50 |
0.38214 | 0 | 6.2 | 0 | 0.504 | 8.04 | 86.5 | 3.2157 | 8 | 307 | 17.4 | 387.38 | 3.13 | 37.6 |
0.41238 | 0 | 6.2 | 0 | 0.504 | 7.163 | 79.9 | 3.2157 | 8 | 307 | 17.4 | 372.08 | 6.36 | 31.6 |
0.44178 | 0 | 6.2 | 0 | 0.504 | 6.552 | 21.4 | 3.3751 | 8 | 307 | 17.4 | 380.34 | 3.76 | 31.5 |
0.537 | 0 | 6.2 | 0 | 0.504 | 5.981 | 68.1 | 3.6715 | 8 | 307 | 17.4 | 378.35 | 11.65 | 24.3 |
0.57529 | 0 | 6.2 | 0 | 0.507 | 8.337 | 73.3 | 3.8384 | 8 | 307 | 17.4 | 385.91 | 2.47 | 41.7 |
0.33147 | 0 | 6.2 | 0 | 0.507 | 8.247 | 70.4 | 3.6519 | 8 | 307 | 17.4 | 378.95 | 3.95 | 48.3 |
0.44791 | 0 | 6.2 | 1 | 0.507 | 6.726 | 66.5 | 3.6519 | 8 | 307 | 17.4 | 360.2 | 8.05 | 29 |
0.33045 | 0 | 6.2 | 0 | 0.507 | 6.086 | 61.5 | 3.6519 | 8 | 307 | 17.4 | 376.75 | 10.88 | 24 |
0.52058 | 0 | 6.2 | 1 | 0.507 | 6.631 | 76.5 | 4.148 | 8 | 307 | 17.4 | 388.45 | 9.54 | 25.1 |
0.11329 | 30 | 4.93 | 0 | 0.428 | 6.897 | 54.3 | 6.3361 | 6 | 300 | 16.6 | 391.25 | 11.38 | 22 |
0.1029 | 30 | 4.93 | 0 | 0.428 | 6.358 | 52.9 | 7.0355 | 6 | 300 | 16.6 | 372.75 | 11.22 | 22.2 |
0.12757 | 30 | 4.93 | 0 | 0.428 | 6.393 | 7.8 | 7.0355 | 6 | 300 | 16.6 | 374.71 | 5.19 | 23.7 |
0.20608 | 22 | 5.86 | 0 | 0.431 | 5.593 | 76.5 | 7.9549 | 7 | 330 | 19.1 | 372.49 | 12.5 | 17.6 |
0.33983 | 22 | 5.86 | 0 | 0.431 | 6.108 | 34.9 | 8.0555 | 7 | 330 | 19.1 | 390.18 | 9.16 | 24.3 |
0.16439 | 22 | 5.86 | 0 | 0.431 | 6.433 | 49.1 | 7.8265 | 7 | 330 | 19.1 | 374.71 | 9.52 | 24.5 |
0.19073 | 22 | 5.86 | 0 | 0.431 | 6.718 | 17.5 | 7.8265 | 7 | 330 | 19.1 | 393.74 | 6.56 | 26.2 |
0.1403 | 22 | 5.86 | 0 | 0.431 | 6.487 | 13 | 7.3967 | 7 | 330 | 19.1 | 396.28 | 5.9 | 24.4 |
0.21409 | 22 | 5.86 | 0 | 0.431 | 6.438 | 8.9 | 7.3967 | 7 | 330 | 19.1 | 377.07 | 3.59 | 24.8 |
0.36894 | 22 | 5.86 | 0 | 0.431 | 8.259 | 8.4 | 8.9067 | 7 | 330 | 19.1 | 396.9 | 3.54 | 42.8 |
0.54011 | 20 | 3.97 | 0 | 0.647 | 7.203 | 81.8 | 2.1121 | 5 | 264 | 13 | 392.8 | 9.59 | 33.8 |
0.53412 | 20 | 3.97 | 0 | 0.647 | 7.52 | 89.4 | 2.1398 | 5 | 264 | 13 | 388.37 | 7.26 | 43.1 |
0.52014 | 20 | 3.97 | 0 | 0.647 | 8.398 | 91.5 | 2.2885 | 5 | 264 | 13 | 386.86 | 5.91 | 48.8 |
0.82526 | 20 | 3.97 | 0 | 0.647 | 7.327 | 94.5 | 2.0788 | 5 | 264 | 13 | 393.42 | 11.25 | 31 |
0.55007 | 20 | 3.97 | 0 | 0.647 | 7.206 | 91.6 | 1.9301 | 5 | 264 | 13 | 387.89 | 8.1 | 36.5 |
0.76162 | 20 | 3.97 | 0 | 0.647 | 5.56 | 62.8 | 1.9865 | 5 | 264 | 13 | 392.4 | 10.45 | 22.8 |
0.7857 | 20 | 3.97 | 0 | 0.647 | 7.014 | 84.6 | 2.1329 | 5 | 264 | 13 | 384.07 | 14.79 | 30.7 |
0.5405 | 20 | 3.97 | 0 | 0.575 | 7.47 | 52.6 | 2.872 | 5 | 264 | 13 | 390.3 | 3.16 | 43.5 |
0.16211 | 20 | 6.96 | 0 | 0.464 | 6.24 | 16.3 | 4.429 | 3 | 223 | 18.6 | 396.9 | 6.59 | 25.2 |
0.1146 | 20 | 6.96 | 0 | 0.464 | 6.538 | 58.7 | 3.9175 | 3 | 223 | 18.6 | 394.96 | 7.73 | 24.4 |
0.22188 | 20 | 6.96 | 1 | 0.464 | 7.691 | 51.8 | 4.3665 | 3 | 223 | 18.6 | 390.77 | 6.58 | 35.2 |
0.05644 | 40 | 6.41 | 1 | 0.447 | 6.758 | 32.9 | 4.0776 | 4 | 254 | 17.6 | 396.9 | 3.53 | 32.4 |
0.21038 | 20 | 3.33 | 0 | 0.4429 | 6.812 | 32.2 | 4.1007 | 5 | 216 | 14.9 | 396.9 | 4.85 | 35.1 |
0.03705 | 20 | 3.33 | 0 | 0.4429 | 6.968 | 37.2 | 5.2447 | 5 | 216 | 14.9 | 392.23 | 4.59 | 35.4 |
0.06129 | 20 | 3.33 | 1 | 0.4429 | 7.645 | 49.7 | 5.2119 | 5 | 216 | 14.9 | 377.07 | 3.01 | 46 |
0.01501 | 90 | 1.21 | 1 | 0.401 | 7.923 | 24.8 | 5.885 | 1 | 198 | 13.6 | 395.52 | 3.16 | 50 |
0.00906 | 90 | 2.97 | 0 | 0.4 | 7.088 | 20.8 | 7.3073 | 1 | 285 | 15.3 | 394.72 | 7.85 | 32.2 |
0.01096 | 55 | 2.25 | 0 | 0.389 | 6.453 | 31.9 | 7.3073 | 1 | 300 | 15.3 | 394.72 | 8.23 | 22 |
0.01965 | 80 | 1.76 | 0 | 0.385 | 6.23 | 31.5 | 9.0892 | 1 | 241 | 18.2 | 341.6 | 12.93 | 20.1 |
0.0459 | 52.5 | 5.32 | 0 | 0.405 | 6.315 | 45.6 | 7.3172 | 6 | 293 | 16.6 | 396.9 | 7.6 | 22.3 |
0.03502 | 80 | 4.95 | 0 | 0.411 | 6.861 | 27.9 | 5.1167 | 4 | 245 | 19.2 | 396.9 | 3.33 | 28.5 |
0.03615 | 80 | 4.95 | 0 | 0.411 | 6.63 | 23.4 | 5.1167 | 4 | 245 | 19.2 | 396.9 | 4.7 | 27.9 |
0.08265 | 0 | 13.92 | 0 | 0.437 | 6.127 | 18.4 | 5.5027 | 4 | 289 | 16 | 396.9 | 8.58 | 23.9 |
0.05372 | 0 | 13.92 | 0 | 0.437 | 6.549 | 51 | 5.9604 | 4 | 289 | 16 | 392.85 | 7.39 | 27.1 |
0.14103 | 0 | 13.92 | 0 | 0.437 | 5.79 | 58 | 6.32 | 4 | 289 | 16 | 396.9 | 15.84 | 20.3 |
0.03537 | 34 | 6.09 | 0 | 0.433 | 6.59 | 40.4 | 5.4917 | 7 | 329 | 16.1 | 395.75 | 9.5 | 22 |
0.09266 | 34 | 6.09 | 0 | 0.433 | 6.495 | 18.4 | 5.4917 | 7 | 329 | 16.1 | 383.61 | 8.67 | 26.4 |
0.1 | 34 | 6.09 | 0 | 0.433 | 6.982 | 17.7 | 5.4917 | 7 | 329 | 16.1 | 390.43 | 4.86 | 33.1 |
0.05515 | 33 | 2.18 | 0 | 0.472 | 7.236 | 41.1 | 4.022 | 7 | 222 | 18.4 | 393.68 | 6.93 | 36.1 |
0.05479 | 33 | 2.18 | 0 | 0.472 | 6.616 | 58.1 | 3.37 | 7 | 222 | 18.4 | 393.36 | 8.93 | 28.4 |
0.07503 | 33 | 2.18 | 0 | 0.472 | 7.42 | 71.9 | 3.0992 | 7 | 222 | 18.4 | 396.9 | 6.47 | 33.4 |
0.49298 | 0 | 9.9 | 0 | 0.544 | 6.635 | 82.5 | 3.3175 | 4 | 304 | 18.4 | 396.9 | 4.54 | 22.8 |
0.3494 | 0 | 9.9 | 0 | 0.544 | 5.972 | 76.7 | 3.1025 | 4 | 304 | 18.4 | 396.24 | 9.97 | 20.3 |
2.63548 | 0 | 9.9 | 0 | 0.544 | 4.973 | 37.8 | 2.5194 | 4 | 304 | 18.4 | 350.45 | 12.64 | 16.1 |
0.79041 | 0 | 9.9 | 0 | 0.544 | 6.122 | 52.8 | 2.6403 | 4 | 304 | 18.4 | 396.9 | 5.98 | 22.1 |
0.26169 | 0 | 9.9 | 0 | 0.544 | 6.023 | 90.4 | 2.834 | 4 | 304 | 18.4 | 396.3 | 11.72 | 19.4 |
0.25356 | 0 | 9.9 | 0 | 0.544 | 5.705 | 77.7 | 3.945 | 4 | 304 | 18.4 | 396.42 | 11.5 | 16.2 |
0.31827 | 0 | 9.9 | 0 | 0.544 | 5.914 | 83.2 | 3.9986 | 4 | 304 | 18.4 | 390.7 | 18.33 | 17.8 |
0.24522 | 0 | 9.9 | 0 | 0.544 | 5.782 | 71.7 | 4.0317 | 4 | 304 | 18.4 | 396.9 | 15.94 | 19.8 |
0.40202 | 0 | 9.9 | 0 | 0.544 | 6.382 | 67.2 | 3.5325 | 4 | 304 | 18.4 | 395.21 | 10.36 | 23.1 |
0.1676 | 0 | 7.38 | 0 | 0.493 | 6.426 | 52.3 | 4.5404 | 5 | 287 | 19.6 | 396.9 | 7.2 | 23.8 |
0.34109 | 0 | 7.38 | 0 | 0.493 | 6.415 | 40.1 | 4.7211 | 5 | 287 | 19.6 | 396.9 | 6.12 | 25 |
0.19186 | 0 | 7.38 | 0 | 0.493 | 6.431 | 14.7 | 5.4159 | 5 | 287 | 19.6 | 393.68 | 5.08 | 24.6 |
0.24103 | 0 | 7.38 | 0 | 0.493 | 6.083 | 43.7 | 5.4159 | 5 | 287 | 19.6 | 396.9 | 12.79 | 22.2 |
0.06617 | 0 | 3.24 | 0 | 0.46 | 5.868 | 25.8 | 5.2146 | 4 | 430 | 16.9 | 382.44 | 9.97 | 19.3 |
0.04544 | 0 | 3.24 | 0 | 0.46 | 6.144 | 32.2 | 5.8736 | 4 | 430 | 16.9 | 368.57 | 9.09 | 19.8 |
0.05083 | 0 | 5.19 | 0 | 0.515 | 6.316 | 38.1 | 6.4584 | 5 | 224 | 20.2 | 389.71 | 5.68 | 22.2 |
0.03738 | 0 | 5.19 | 0 | 0.515 | 6.31 | 38.5 | 6.4584 | 5 | 224 | 20.2 | 389.4 | 6.75 | 20.7 |
0.03427 | 0 | 5.19 | 0 | 0.515 | 5.869 | 46.3 | 5.2311 | 5 | 224 | 20.2 | 396.9 | 9.8 | 19.5 |
0.03306 | 0 | 5.19 | 0 | 0.515 | 6.059 | 37.3 | 4.8122 | 5 | 224 | 20.2 | 396.14 | 8.51 | 20.6 |
0.05497 | 0 | 5.19 | 0 | 0.515 | 5.985 | 45.4 | 4.8122 | 5 | 224 | 20.2 | 396.9 | 9.74 | 19 |
0.06151 | 0 | 5.19 | 0 | 0.515 | 5.968 | 58.5 | 4.8122 | 5 | 224 | 20.2 | 396.9 | 9.29 | 18.7 |
0.01301 | 35 | 1.52 | 0 | 0.442 | 7.241 | 49.3 | 7.0379 | 1 | 284 | 15.5 | 394.74 | 5.49 | 32.7 |
0.02498 | 0 | 1.89 | 0 | 0.518 | 6.54 | 59.7 | 6.2669 | 1 | 422 | 15.9 | 389.96 | 8.65 | 16.5 |
0.02543 | 55 | 3.78 | 0 | 0.484 | 6.696 | 56.4 | 5.7321 | 5 | 370 | 17.6 | 396.9 | 7.18 | 23.9 |
0.03049 | 55 | 3.78 | 0 | 0.484 | 6.874 | 28.1 | 6.4654 | 5 | 370 | 17.6 | 387.97 | 4.61 | 31.2 |
0.0187 | 85 | 4.15 | 0 | 0.429 | 6.516 | 27.7 | 8.5353 | 4 | 351 | 17.9 | 392.43 | 6.36 | 23.1 |
0.01501 | 80 | 2.01 | 0 | 0.435 | 6.635 | 29.7 | 8.344 | 4 | 280 | 17 | 390.94 | 5.99 | 24.5 |
0.02899 | 40 | 1.25 | 0 | 0.429 | 6.939 | 34.5 | 8.7921 | 1 | 335 | 19.7 | 389.85 | 5.89 | 26.6 |
0.07244 | 60 | 1.69 | 0 | 0.411 | 5.884 | 18.5 | 10.7103 | 4 | 411 | 18.3 | 392.33 | 7.79 | 18.6 |
8.98296 | 0 | 18.1 | 1 | 0.77 | 6.212 | 97.4 | 2.1222 | 24 | 666 | 20.2 | 377.73 | 17.6 | 17.8 |
3.8497 | 0 | 18.1 | 1 | 0.77 | 6.395 | 91 | 2.5052 | 24 | 666 | 20.2 | 391.34 | 13.27 | 21.7 |
5.20177 | 0 | 18.1 | 1 | 0.77 | 6.127 | 83.4 | 2.7227 | 24 | 666 | 20.2 | 395.43 | 11.48 | 22.7 |
4.26131 | 0 | 18.1 | 0 | 0.77 | 6.112 | 81.3 | 2.5091 | 24 | 666 | 20.2 | 390.74 | 12.67 | 22.6 |
4.54192 | 0 | 18.1 | 0 | 0.77 | 6.398 | 88 | 2.5182 | 24 | 666 | 20.2 | 374.56 | 7.79 | 25 |
3.67822 | 0 | 18.1 | 0 | 0.77 | 5.362 | 96.2 | 2.1036 | 24 | 666 | 20.2 | 380.79 | 10.19 | 20.8 |
4.55587 | 0 | 18.1 | 0 | 0.718 | 3.561 | 87.9 | 1.6132 | 24 | 666 | 20.2 | 354.7 | 7.12 | 27.5 |
3.69695 | 0 | 18.1 | 0 | 0.718 | 4.963 | 91.4 | 1.7523 | 24 | 666 | 20.2 | 316.03 | 14 | 21.9 |
13.5222 | 0 | 18.1 | 0 | 0.631 | 3.863 | 100 | 1.5106 | 24 | 666 | 20.2 | 131.42 | 13.33 | 23.1 |
4.89822 | 0 | 18.1 | 0 | 0.631 | 4.97 | 100 | 1.3325 | 24 | 666 | 20.2 | 375.52 | 3.26 | 50 |
6.53876 | 0 | 18.1 | 1 | 0.631 | 7.016 | 97.5 | 1.2024 | 24 | 666 | 20.2 | 392.05 | 2.96 | 50 |
9.2323 | 0 | 18.1 | 0 | 0.631 | 6.216 | 100 | 1.1691 | 24 | 666 | 20.2 | 366.15 | 9.53 | 50 |
8.26725 | 0 | 18.1 | 1 | 0.668 | 5.875 | 89.6 | 1.1296 | 24 | 666 | 20.2 | 347.88 | 8.88 | 50 |
11.1081 | 0 | 18.1 | 0 | 0.668 | 4.906 | 100 | 1.1742 | 24 | 666 | 20.2 | 396.9 | 34.77 | 13.8 |
18.4982 | 0 | 18.1 | 0 | 0.668 | 4.138 | 100 | 1.137 | 24 | 666 | 20.2 | 396.9 | 37.97 | 13.8 |
15.288 | 0 | 18.1 | 0 | 0.671 | 6.649 | 93.3 | 1.3449 | 24 | 666 | 20.2 | 363.02 | 23.24 | 13.9 |
9.82349 | 0 | 18.1 | 0 | 0.671 | 6.794 | 98.8 | 1.358 | 24 | 666 | 20.2 | 396.9 | 21.24 | 13.3 |
9.18702 | 0 | 18.1 | 0 | 0.7 | 5.536 | 100 | 1.5804 | 24 | 666 | 20.2 | 396.9 | 23.6 | 11.3 |
7.99248 | 0 | 18.1 | 0 | 0.7 | 5.52 | 100 | 1.5331 | 24 | 666 | 20.2 | 396.9 | 24.56 | 12.3 |
20.0849 | 0 | 18.1 | 0 | 0.7 | 4.368 | 91.2 | 1.4395 | 24 | 666 | 20.2 | 285.83 | 30.63 | 8.8 |
24.3938 | 0 | 18.1 | 0 | 0.7 | 4.652 | 100 | 1.4672 | 24 | 666 | 20.2 | 396.9 | 28.28 | 10.5 |
22.5971 | 0 | 18.1 | 0 | 0.7 | 5 | 89.5 | 1.5184 | 24 | 666 | 20.2 | 396.9 | 31.99 | 7.4 |
8.15174 | 0 | 18.1 | 0 | 0.7 | 5.39 | 98.9 | 1.7281 | 24 | 666 | 20.2 | 396.9 | 20.85 | 11.5 |
5.29305 | 0 | 18.1 | 0 | 0.7 | 6.051 | 82.5 | 2.1678 | 24 | 666 | 20.2 | 378.38 | 18.76 | 23.2 |
11.5779 | 0 | 18.1 | 0 | 0.7 | 5.036 | 97 | 1.77 | 24 | 666 | 20.2 | 396.9 | 25.68 | 9.7 |
13.3598 | 0 | 18.1 | 0 | 0.693 | 5.887 | 94.7 | 1.7821 | 24 | 666 | 20.2 | 396.9 | 16.35 | 12.7 |
5.87205 | 0 | 18.1 | 0 | 0.693 | 6.405 | 96 | 1.6768 | 24 | 666 | 20.2 | 396.9 | 19.37 | 12.5 |
38.3518 | 0 | 18.1 | 0 | 0.693 | 5.453 | 100 | 1.4896 | 24 | 666 | 20.2 | 396.9 | 30.59 | 5 |
25.0461 | 0 | 18.1 | 0 | 0.693 | 5.987 | 100 | 1.5888 | 24 | 666 | 20.2 | 396.9 | 26.77 | 5.6 |
14.2362 | 0 | 18.1 | 0 | 0.693 | 6.343 | 100 | 1.5741 | 24 | 666 | 20.2 | 396.9 | 20.32 | 7.2 |
24.8017 | 0 | 18.1 | 0 | 0.693 | 5.349 | 96 | 1.7028 | 24 | 666 | 20.2 | 396.9 | 19.77 | 8.3 |
11.9511 | 0 | 18.1 | 0 | 0.659 | 5.608 | 100 | 1.2852 | 24 | 666 | 20.2 | 332.09 | 12.13 | 27.9 |
7.40389 | 0 | 18.1 | 0 | 0.597 | 5.617 | 97.9 | 1.4547 | 24 | 666 | 20.2 | 314.64 | 26.4 | 17.2 |
28.6558 | 0 | 18.1 | 0 | 0.597 | 5.155 | 100 | 1.5894 | 24 | 666 | 20.2 | 210.97 | 20.08 | 16.3 |
45.7461 | 0 | 18.1 | 0 | 0.693 | 4.519 | 100 | 1.6582 | 24 | 666 | 20.2 | 88.27 | 36.98 | 7 |
18.0846 | 0 | 18.1 | 0 | 0.679 | 6.434 | 100 | 1.8347 | 24 | 666 | 20.2 | 27.25 | 29.05 | 7.2 |
25.9406 | 0 | 18.1 | 0 | 0.679 | 5.304 | 89.1 | 1.6475 | 24 | 666 | 20.2 | 127.36 | 26.64 | 10.4 |
73.5341 | 0 | 18.1 | 0 | 0.679 | 5.957 | 100 | 1.8026 | 24 | 666 | 20.2 | 16.45 | 20.62 | 8.8 |
11.8123 | 0 | 18.1 | 0 | 0.718 | 6.824 | 76.5 | 1.794 | 24 | 666 | 20.2 | 48.45 | 22.74 | 8.4 |
8.79212 | 0 | 18.1 | 0 | 0.584 | 5.565 | 70.6 | 2.0635 | 24 | 666 | 20.2 | 3.65 | 17.16 | 11.7 |
15.8603 | 0 | 18.1 | 0 | 0.679 | 5.896 | 95.4 | 1.9096 | 24 | 666 | 20.2 | 7.68 | 24.39 | 8.3 |
37.6619 | 0 | 18.1 | 0 | 0.679 | 6.202 | 78.7 | 1.8629 | 24 | 666 | 20.2 | 18.82 | 14.52 | 10.9 |
7.36711 | 0 | 18.1 | 0 | 0.679 | 6.193 | 78.1 | 1.9356 | 24 | 666 | 20.2 | 96.73 | 21.52 | 11 |
9.33889 | 0 | 18.1 | 0 | 0.679 | 6.38 | 95.6 | 1.9682 | 24 | 666 | 20.2 | 60.72 | 24.08 | 9.5 |
10.0623 | 0 | 18.1 | 0 | 0.584 | 6.833 | 94.3 | 2.0882 | 24 | 666 | 20.2 | 81.33 | 19.69 | 14.1 |
6.44405 | 0 | 18.1 | 0 | 0.584 | 6.425 | 74.8 | 2.2004 | 24 | 666 | 20.2 | 97.95 | 12.03 | 16.1 |
5.58107 | 0 | 18.1 | 0 | 0.713 | 6.436 | 87.9 | 2.3158 | 24 | 666 | 20.2 | 100.19 | 16.22 | 14.3 |
13.9134 | 0 | 18.1 | 0 | 0.713 | 6.208 | 95 | 2.2222 | 24 | 666 | 20.2 | 100.63 | 15.17 | 11.7 |
15.1772 | 0 | 18.1 | 0 | 0.74 | 6.152 | 100 | 1.9142 | 24 | 666 | 20.2 | 9.32 | 26.45 | 8.7 |
9.39063 | 0 | 18.1 | 0 | 0.74 | 5.627 | 93.9 | 1.8172 | 24 | 666 | 20.2 | 396.9 | 22.88 | 12.8 |
22.0511 | 0 | 18.1 | 0 | 0.74 | 5.818 | 92.4 | 1.8662 | 24 | 666 | 20.2 | 391.45 | 22.11 | 10.5 |
9.72418 | 0 | 18.1 | 0 | 0.74 | 6.406 | 97.2 | 2.0651 | 24 | 666 | 20.2 | 385.96 | 19.52 | 17.1 |
5.66637 | 0 | 18.1 | 0 | 0.74 | 6.219 | 100 | 2.0048 | 24 | 666 | 20.2 | 395.69 | 16.59 | 18.4 |
9.96654 | 0 | 18.1 | 0 | 0.74 | 6.485 | 100 | 1.9784 | 24 | 666 | 20.2 | 386.73 | 18.85 | 15.4 |
12.8023 | 0 | 18.1 | 0 | 0.74 | 5.854 | 96.6 | 1.8956 | 24 | 666 | 20.2 | 240.52 | 23.79 | 10.8 |
10.6718 | 0 | 18.1 | 0 | 0.74 | 6.459 | 94.8 | 1.9879 | 24 | 666 | 20.2 | 43.06 | 23.98 | 11.8 |
9.92485 | 0 | 18.1 | 0 | 0.74 | 6.251 | 96.6 | 2.198 | 24 | 666 | 20.2 | 388.52 | 16.44 | 12.6 |
9.32909 | 0 | 18.1 | 0 | 0.713 | 6.185 | 98.7 | 2.2616 | 24 | 666 | 20.2 | 396.9 | 18.13 | 14.1 |
5.44114 | 0 | 18.1 | 0 | 0.713 | 6.655 | 98.2 | 2.3552 | 24 | 666 | 20.2 | 355.29 | 17.73 | 15.2 |
5.09017 | 0 | 18.1 | 0 | 0.713 | 6.297 | 91.8 | 2.3682 | 24 | 666 | 20.2 | 385.09 | 17.27 | 16.1 |
8.24809 | 0 | 18.1 | 0 | 0.713 | 7.393 | 99.3 | 2.4527 | 24 | 666 | 20.2 | 375.87 | 16.74 | 17.8 |
4.75237 | 0 | 18.1 | 0 | 0.713 | 6.525 | 86.5 | 2.4358 | 24 | 666 | 20.2 | 50.92 | 18.13 | 14.1 |
8.20058 | 0 | 18.1 | 0 | 0.713 | 5.936 | 80.3 | 2.7792 | 24 | 666 | 20.2 | 3.5 | 16.94 | 13.5 |
7.75223 | 0 | 18.1 | 0 | 0.713 | 6.301 | 83.7 | 2.7831 | 24 | 666 | 20.2 | 272.21 | 16.23 | 14.9 |
6.80117 | 0 | 18.1 | 0 | 0.713 | 6.081 | 84.4 | 2.7175 | 24 | 666 | 20.2 | 396.9 | 14.7 | 20 |
4.81213 | 0 | 18.1 | 0 | 0.713 | 6.701 | 90 | 2.5975 | 24 | 666 | 20.2 | 255.23 | 16.42 | 16.4 |
3.69311 | 0 | 18.1 | 0 | 0.713 | 6.376 | 88.4 | 2.5671 | 24 | 666 | 20.2 | 391.43 | 14.65 | 17.7 |
6.65492 | 0 | 18.1 | 0 | 0.713 | 6.317 | 83 | 2.7344 | 24 | 666 | 20.2 | 396.9 | 13.99 | 19.5 |
5.82115 | 0 | 18.1 | 0 | 0.713 | 6.513 | 89.9 | 2.8016 | 24 | 666 | 20.2 | 393.82 | 10.29 | 20.2 |
7.83932 | 0 | 18.1 | 0 | 0.655 | 6.209 | 65.4 | 2.9634 | 24 | 666 | 20.2 | 396.9 | 13.22 | 21.4 |
3.1636 | 0 | 18.1 | 0 | 0.655 | 5.759 | 48.2 | 3.0665 | 24 | 666 | 20.2 | 334.4 | 14.13 | 19.9 |
3.77498 | 0 | 18.1 | 0 | 0.655 | 5.952 | 84.7 | 2.8715 | 24 | 666 | 20.2 | 22.01 | 17.15 | 19 |
4.42228 | 0 | 18.1 | 0 | 0.584 | 6.003 | 94.5 | 2.5403 | 24 | 666 | 20.2 | 331.29 | 21.32 | 19.1 |
15.5757 | 0 | 18.1 | 0 | 0.58 | 5.926 | 71 | 2.9084 | 24 | 666 | 20.2 | 368.74 | 18.13 | 19.1 |
13.0751 | 0 | 18.1 | 0 | 0.58 | 5.713 | 56.7 | 2.8237 | 24 | 666 | 20.2 | 396.9 | 14.76 | 20.1 |
4.03841 | 0 | 18.1 | 0 | 0.532 | 6.229 | 90.7 | 3.0993 | 24 | 666 | 20.2 | 395.33 | 12.87 | 19.6 |
3.56868 | 0 | 18.1 | 0 | 0.58 | 6.437 | 75 | 2.8965 | 24 | 666 | 20.2 | 393.37 | 14.36 | 23.2 |
8.05579 | 0 | 18.1 | 0 | 0.584 | 5.427 | 95.4 | 2.4298 | 24 | 666 | 20.2 | 352.58 | 18.14 | 13.8 |
4.87141 | 0 | 18.1 | 0 | 0.614 | 6.484 | 93.6 | 2.3053 | 24 | 666 | 20.2 | 396.21 | 18.68 | 16.7 |
15.0234 | 0 | 18.1 | 0 | 0.614 | 5.304 | 97.3 | 2.1007 | 24 | 666 | 20.2 | 349.48 | 24.91 | 12 |
10.233 | 0 | 18.1 | 0 | 0.614 | 6.185 | 96.7 | 2.1705 | 24 | 666 | 20.2 | 379.7 | 18.03 | 14.6 |
14.3337 | 0 | 18.1 | 0 | 0.614 | 6.229 | 88 | 1.9512 | 24 | 666 | 20.2 | 383.32 | 13.11 | 21.4 |
5.82401 | 0 | 18.1 | 0 | 0.532 | 6.242 | 64.7 | 3.4242 | 24 | 666 | 20.2 | 396.9 | 10.74 | 23 |
5.70818 | 0 | 18.1 | 0 | 0.532 | 6.75 | 74.9 | 3.3317 | 24 | 666 | 20.2 | 393.07 | 7.74 | 23.7 |
2.81838 | 0 | 18.1 | 0 | 0.532 | 5.762 | 40.3 | 4.0983 | 24 | 666 | 20.2 | 392.92 | 10.42 | 21.8 |
2.37857 | 0 | 18.1 | 0 | 0.583 | 5.871 | 41.9 | 3.724 | 24 | 666 | 20.2 | 370.73 | 13.34 | 20.6 |
5.69175 | 0 | 18.1 | 0 | 0.583 | 6.114 | 79.8 | 3.5459 | 24 | 666 | 20.2 | 392.68 | 14.98 | 19.1 |
4.83567 | 0 | 18.1 | 0 | 0.583 | 5.905 | 53.2 | 3.1523 | 24 | 666 | 20.2 | 388.22 | 11.45 | 20.6 |
0.15086 | 0 | 27.74 | 0 | 0.609 | 5.454 | 92.7 | 1.8209 | 4 | 711 | 20.1 | 395.09 | 18.06 | 15.2 |
0.20746 | 0 | 27.74 | 0 | 0.609 | 5.093 | 98 | 1.8226 | 4 | 711 | 20.1 | 318.43 | 29.68 | 8.1 |
0.10574 | 0 | 27.74 | 0 | 0.609 | 5.983 | 98.8 | 1.8681 | 4 | 711 | 20.1 | 390.11 | 18.07 | 13.6 |
0.11132 | 0 | 27.74 | 0 | 0.609 | 5.983 | 83.5 | 2.1099 | 4 | 711 | 20.1 | 396.9 | 13.35 | 20.1 |
0.17331 | 0 | 9.69 | 0 | 0.585 | 5.707 | 54 | 2.3817 | 6 | 391 | 19.2 | 396.9 | 12.01 | 21.8 |
0.26838 | 0 | 9.69 | 0 | 0.585 | 5.794 | 70.6 | 2.8927 | 6 | 391 | 19.2 | 396.9 | 14.1 | 18.3 |
0.17783 | 0 | 9.69 | 0 | 0.585 | 5.569 | 73.5 | 2.3999 | 6 | 391 | 19.2 | 395.77 | 15.1 | 17.5 |
0.06263 | 0 | 11.93 | 0 | 0.573 | 6.593 | 69.1 | 2.4786 | 1 | 273 | 21 | 391.99 | 9.67 | 22.4 |
0.04527 | 0 | 11.93 | 0 | 0.573 | 6.12 | 76.7 | 2.2875 | 1 | 273 | 21 | 396.9 | 9.08 | 20.6 |
0.06076 | 0 | 11.93 | 0 | 0.573 | 6.976 | 91 | 2.1675 | 1 | 273 | 21 | 396.9 | 5.64 | 23.9 |
0.04741 | 0 | 11.93 | 0 | 0.573 | 6.03 | 80.8 | 2.505 | 1 | 273 | 21 | 396.9 | 7.88 | 11.9 |
Code để đọc và xử lý data. Với dữ liệu nhà Boston, chúng ta cần chuẩn hóa dữ liệu vì các cột dữ liệu có đơn vị dữ liệu khác nhau và các giá trị phân bố khác nhau. (Sau khi làm xong ví dụ này, các bạn hãy chạy thử chương trình khi data không được chuẩn hóa, và quan sát, so sánh kết quả chương trình gốc).
import pandas as pd import numpy as np import matplotlib.pyplot as plt data = pd.read_csv('BostonHousing.csv') def normal(x:list): maxi = max(x) mini = min(x) avg = np.mean(x) new = [(i-avg)/(maxi-mini) for i in x ] return new df = data.copy() df = df.apply(normal, axis=0) Xd = df.drop(columns=['medv']) Xd.insert(0, 'X0', 1) # bias # numpy array format y = df.medv.values X = Xd.values # sample size m = len(df.index) n = X.shape[1] theta = np.ones(n)
Cài theo cách dùng chỉ mục index
# No Vectorization - batch gradien descent # cost function def cost_loop(theta = theta, x=X, y=y, m=m, n=n): cost = 0 for i in range(m): hypo_i = 0 for j in range(n): hypo_i += theta[j]*X[i,j] cost_i = (hypo_i - y[i])**2 cost += cost_i cost = (1/m)*cost return cost # training learning_rate = 0.01 theta = np.ones(n) cost_list = [] for itr in range(500): dev_list = [] for k in range(n): dev_sum = 0 for i in range(m): hypo_i = 0 for j in range(n): hypo_i += theta[j]*X[i,j] dev_i = (hypo_i - y[i])*X[i,k] dev_sum += dev_i dev_sum = (2/m)*dev_sum dev_list.append(dev_sum) theta = theta - learning_rate*np.array(dev_list) cost_val = cost_loop(theta) cost_list.append(cost_val) plt.plot(np.arange(0, 500),cost_list) plt.xlabel('epoch') plt.ylabel('Giá trị loss')
Giá trị loss qua các vòng lặp
Cài theo phương pháp vectorization
# Vectorization # Initialize theta theta = np.ones(n) def cost(theta, X=X, y=y, m=m): cost = np.dot(np.dot(X,theta) - y, np.dot(X,theta) - y) cost = (1/m)*cost return cost # learning rate learning_rate = 0.01 theta = np.ones(n) cost_list = [] for i in range(500): output = np.dot(X,theta) loss_grd = output - y gradients = (2/m)*np.dot(np.transpose(X), loss_grd) theta = theta - learning_rate*gradients cost_val = cost(theta) cost_list.append(cost_val) plt.plot(np.arange(0, 500),cost_list) plt.xlabel('epoch') plt.ylabel('Giá trị loss')
Giá trị loss qua các vòng lặp
Ở ví dụ này, khi chạy hai đoạn code để huấn luyện mô hình, chúng ta dễ dạng nhận ra cách cài đặt theo vectorization nhanh hơn rất nhiều so với cách dùng chỉ mục index thông thường.
Thật may mắn là chúng ta không cần phải là siêu sao coding để cài được những chương trình dùng kỹ thuật vectorization. Các thư viện phổ biến hiện nay đã làm những phần việc này. Khi các bạn muốn xây dựng một hàm hay thực hiện một tác vụ nào đó, các bạn nên dùng những hàm có sẵn trong thư viện (nếu có) vì code chúng ta cài thường tệ hơn code trong các thư viện ^^.