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吳恩達深度學習第一課第四周作業及學習心得體會,含三元分類問題解決!

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#?-*-?coding:?utf-8?-*-
“““
Created?on?Thu?Jul?19?21:22:04?2018

@author:?yuanye
“““



import?numpy?as?np
import?matplotlib.pyplot?as?plt
from?sklearn.linear_model?import?LogisticRegression

#產生數據
np.random.seed(1)
m?=?600?????????????????????????????????#樣本數
N?=?int(m/2)????????????????????????????#分為兩類
D?=?2???????????????????????????????????#樣本的特征數或維度
X?=?np.zeros((mD))?????????????????????#初始化樣本坐標
Y?=?np.zeros((m1))?????????????????????#初始化樣本標簽
a?=?4???????????????????????????????????#基礎半徑

for?j?in?range(2):
????ix?=?range(N*jN*(j+1))#ix=(0,199)(200,399)
????t?=?np.linspace(j*3.12(j+1)*3.12N)????????????????????????????#theta角度,產生200個角度并加入隨機數,保證角度隨機分開,圖像開起來稀疏程度不一
????r?=?a*np.sin(4*t)?+?np.random.randn(N)*0.2??????????????????????#radius半徑,4sin(4*t)并加入一定的隨機,圖像軌道不平滑
????X[ix]?=?np.c_[r*np.sin(t)?r*np.cos(t)]?????????????????????????#生成坐標點
????Y[ix]?=?j???????????????????????????????????????????????????????#red?or?blue


X?=?X.T
Y?=?Y.T
log?=?LogisticRegression(C=2000)
log.fit(X.TY.ravel())??????????????????????#用X和Y來進行邏輯回歸訓練

y_log_predict?=?log.predict(X.T)????????????#根據訓練結果對X進行預測
p_log?=?np.mean(y_log_predict==Y.ravel())???#計算準確率
print(‘邏輯回歸的準確率為:%f‘%p_log)

x_min?x_max?=?X[0?:].min()?-?1?X[0?:].max()?+?1
y_min?y_max?=?X[1?:].min()?-?1?X[1?:].max()?+?1
xx?yy?=?np.meshgrid(np.arange(x_min?x_max?0.01)np.arange(y_min?y_max?0.01))?#將二維平面以0.01*0.01的間隔散開,xx為每個點的橫坐標,yy為每個點的縱坐標
zz?=?np.array([xx.ravel()?yy.ravel()]).T???#zz為每個點的橫縱坐標,其行數為總點數,列數為特征數,即維度
Z?=?log.predict(zz)?????????????????????????#通過logistic回歸預測每個點的標簽
Z?=?Z.reshape(xx.shape)
plt.figure(1)
plt.scatter(X[0?:]?X[1?:]?c=np.squeeze(Y)?edgecolors=‘k‘?s=40?cmap=plt.cm.Spectral)
plt.contourf(xx?yy?Z?alpha=0.3cmap=plt.cm.Spectral)?#繪制等高線
plt.xlim(xx.min()?xx.max())
plt.ylim(yy.min()?yy.max())
plt.show()



#初始化參數
def?init_para(layer_dims):
????L?=?len(layer_dims)?????????????#L為總層數
????np.random.seed(L)
????parameters?=?{}
????for?l?in?range(1L):????????????#初始化W1~WLb1~bL
????????parameters[‘W‘+str(l)]?=?np.random.randn(layer_dims[l]?layer_dims[l-1])*0.01
????????parameters[‘b‘+str(l)]?=?np.zeros((layer_dims[l]?1))
????return?parameters

#單次前向運算
def?single_forward(A_pre?W?b?mode):
????Z?=?np.dot(W?A_pre)?+?b????????#根據上一層的輸出A_pre,以及本層的W?b計算本層的Z
????if?mode==‘sigmoid‘:?????????????#根據所選定的激活函數計算本層的輸出
????????A?=?1.0/(1+np.exp(-Z))
????if?mode==‘ReLU‘:
????????A?=?(Z+abs(Z))/2
????if?mode==‘tanh‘:
????????A?=?np.tanh(Z)
????cache?=?{‘A_pre‘:A_pre
?????????????‘W‘:W
?????????????‘b‘:b
?????????????‘Z‘:Z
?????????????‘A‘:A}
????return?A?cache

#前向傳播函數
def?prop_forward(X?parameters):
????caches?=?[]
????A?=?X???????????????????????????#將X賦給A0
????L?=?len(parameters)//2
????for?l?in?range(1L):????????????#l從1到L-1,調用L-1次前向運算,由于A0的特征值存在大量負數,
????????A_pre?=?A???????????????????#因此第一層激活函數如果選用ReLU無法正確訓練網絡,因為大量的信息被截掉
????????Acache?=?single_forward(A_pre?parameters

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????7855??2018-07-27?00:00??neuralnetwork_Llayer_2.py
?????文件????????8532??2018-07-27?00:06??neuralnetwork_Llayer_3_ny_equal_3.py
?????文件??????721572??2018-07-27?00:22??吳恩達第一課第四周學習心得體會.docx
?????文件??????598050??2018-07-27?00:22??吳恩達第一課第四周學習心得體會.pdf
?????目錄???????????0??2018-07-26?21:54??CatRecognition_Llayer\
?????文件????????9447??2018-07-26?00:14??CatRecognition_Llayer\CatRecognition_NN_Llayer.py
?????目錄???????????0??2018-07-26?21:54??CatRecognition_Llayer\datasets\
?????文件??????616958??2017-09-02?17:29??CatRecognition_Llayer\datasets\test_catvnoncat.h5
?????文件?????2572022??2017-09-02?17:30??CatRecognition_Llayer\datasets\train_catvnoncat.h5
?????目錄???????????0??2018-07-26?21:54??CatRecognition_Llayer\images\
?????文件??????601084??2017-09-02?17:31??CatRecognition_Llayer\images\cat1.jpg
?????文件??????954514??2018-07-15?21:31??CatRecognition_Llayer\images\cat2.jpg
?????文件???????19441??2017-12-09?22:44??CatRecognition_Llayer\images\cat3.jpg
?????文件???????94439??2017-09-02?17:32??CatRecognition_Llayer\images\cat4.jpg
?????文件???????64278??2018-07-15?21:29??CatRecognition_Llayer\images\cat5.jpg
?????文件??????129629??2018-07-15?21:30??CatRecognition_Llayer\images\cat6.jpg
?????文件???????90920??2018-07-15?21:30??CatRecognition_Llayer\images\cat7.jpg
?????文件??????310181??2017-09-02?17:31??CatRecognition_Llayer\images\other1.jpg
?????文件??????339673??2017-09-02?17:32??CatRecognition_Llayer\images\other2.jpg
?????文件??????636273??2017-09-02?17:32??CatRecognition_Llayer\images\other3.jpg
?????文件???????17997??2017-12-09?22:46??CatRecognition_Llayer\images\other4.jpg
?????文件???????35351??2018-07-15?21:28??CatRecognition_Llayer\images\other5.jpg
?????文件???????41561??2018-07-15?21:31??CatRecognition_Llayer\images\other6.jpg
?????文件???????73296??2018-07-15?21:31??CatRecognition_Llayer\images\other7.jpg
?????文件????????7899??2018-07-26?23:57??neuralnetwork_Llayer_1.py

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