From d9c7678fa214d4e4421698302a7fca686e004ce5 Mon Sep 17 00:00:00 2001 From: bushuhui Date: Mon, 21 Oct 2019 09:09:38 +0800 Subject: [PATCH] Add multi-class dataset for neural network homework --- homework_05_nn/README.md | 45 +- homework_05_nn/dataset_circles.csv | 800 +++++++++++------------ homework_05_nn/images/dataset_digits.png | Bin 0 -> 66406 bytes 3 files changed, 436 insertions(+), 409 deletions(-) create mode 100644 homework_05_nn/images/dataset_digits.png diff --git a/homework_05_nn/README.md b/homework_05_nn/README.md index 1f3e6a3..454a054 100644 --- a/homework_05_nn/README.md +++ b/homework_05_nn/README.md @@ -1,19 +1,27 @@ # Neural Networks -自己编程实现两层或多层全连接神经网络，可以使用`moons` 或者`circles`数据集来测试、验证算法。 +自己编程实现两层或多层全连接神经网络，可以使用`moons` 、`circles`、或者`digits`数据集来测试、验证算法。 -dataset_moons: +**dataset_moons**: ![dataset_moons](images/dataset_moon.png) -dataset_circles: +**dataset_circles**: ![dataset_circles](images/dataset_circle.png) + + +**dataset_digits**: + +![dataset_digits](images/dataset_digits.png) + + + 加载数据的方式是： ```python # moon dataset @@ -33,13 +41,32 @@ plt.show() dataset_circles的数据文件是`dataset_circles.csv` +dataset_digits的加载方式： +```python +import matplotlib.pyplot as plt +from sklearn.datasets import load_digits + +# load data +digits = load_digits() + +# copied from notebook 02_sklearn_data.ipynb +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])) +``` +**要求**： -要求： - -1. 自己编程实现多层全连接神经网络的多分类。 -2. 先用函数的方式实现网络的正向计算和反向误差传播，权值更新。 -3. 构思并实现基于类的神经网络程序。 +1. 先用函数的方式实现网络的正向计算和反向误差传播，权值更新。 +2. 构思并实现基于类的神经网络程序。 +3. 构建多分类的网络（可以使用`dataset_digits`） 4. 学习`softmax`和`cross entropy`的方法，并实现类别所属概率的输出。 5. 对比自己实现与sklearn的方法的精度。 -6. 如何将分类错误的样本可视化出来？ \ No newline at end of file +6. 如何将分类错误的样本可视化出来？ diff --git a/homework_05_nn/dataset_circles.csv b/homework_05_nn/dataset_circles.csv index c0a2404..8304452 100644 --- a/homework_05_nn/dataset_circles.csv +++ b/homework_05_nn/dataset_circles.csv @@ -1,400 +1,400 @@ -9.862597006109558251e+00,4.388945920860357397e+00,0.000000000000000000e+00 -2.877170945049199346e+00,1.202827750793628248e+01,0.000000000000000000e+00 -3.337256239136289437e+00,-5.220370923066885105e+00,0.000000000000000000e+00 -6.493095562032711321e+00,-1.113144595320488328e+01,0.000000000000000000e+00 -9.160816030038004598e+00,-1.009779300537452151e+01,0.000000000000000000e+00 -1.041802753742201126e+01,1.894574992636611332e+00,0.000000000000000000e+00 --9.011386818141570387e+00,7.113786261861553051e+00,0.000000000000000000e+00 -8.634194767050646035e+00,6.044937306977867797e-01,0.000000000000000000e+00 --8.310295927199726762e+00,-1.184857079692059001e+00,0.000000000000000000e+00 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