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add homework 4 - logistic regression
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# Logistic Regression | ||
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自己编程实现Logistic Regression的多分类问题。使用的数据可以是sklearn的digital数据。 | ||
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![digit](images/digit.png) | ||
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加载数据的方式是: | ||
``` | ||
import matplotlib.pyplot as plt | ||
from sklearn.datasets import load_digits | ||
# load data | ||
digits = load_digits() | ||
# plot the digits | ||
fig = plt.figure(figsize=(6, 6)) # figure size in inches | ||
fig.subplots_adjust(left=0, right=1, bottom=0, top=1, hspace=0.05, wspace=0.05) | ||
# plot the digits: each image is 8x8 pixels | ||
for i in range(64): | ||
ax = fig.add_subplot(8, 8, i + 1, xticks=[], yticks=[]) | ||
ax.imshow(digits.images[i], cmap=plt.cm.binary) | ||
# label the image with the target value | ||
ax.text(0, 7, str(digits.target[i])) | ||
``` | ||
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要求: | ||
1. 自己编程实现Logistic Regression的多分了。 | ||
2. 对比自己实现与sklearn的方法的精度。 | ||
3. 如何将分类错误的样本可视化出来? |
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