import?numpy?as?np
from?sklearn?import?preprocessing
from?numpy?import?random
from?sklearn.datasets?import?load_iris
from?sklearn.model_selection?import?train_test_split
import?pandas?as?pd

def?show_accuracy（predictLabelLabel）:
????Label?=?np.ravel（Label）.tolist（）
????predictLabel?=?predictLabel.tolist（）
????count?=?0
????for?i?in?range（len（Label））:
????????if?Label[i]?==?predictLabel[i]:
????????????count?+=?1
????return?（round（count/len（Label）5））

class?node_generator:
????def?__init__（selfwhiten?=?False）:
????????self.Wlist?=?[]
????????self.blist?=?[]
????????self.nonlinear?=?0
????????self.whiten?=?whiten
????
????def?sigmoid（selfdata）:
????????return?1.0/（1+np.exp（-data））
????
????def?linear（selfdata）:
????????return?data
????
????def?tanh（selfdata）:
????????return?（np.exp（data）-np.exp（-data））/（np.exp（data）+np.exp（-data））
????
????def?relu（selfdata）:
????????return?np.maximum（data0）
????
????def?orth（selfW）:
????????for?i?in?range（0W.shape[1]）:
????????????w?=?np.mat（W[:i].copy（））.T
????????????w_sum?=?0
????????????for?j?in?range（i）:
????????????????wj?=?np.mat（W[:j].copy（））.T
????????????????w_sum?+=?（w.T.dot（wj））[00]*wj?
????????????w?-=?w_sum
????????????w?=?w/np.sqrt（w.T.dot（w））
????????????W[:i]?=?np.ravel（w）
????????return?W
????????
????def?generator（selfshapetimes）:
????????for?i?in?range（times）:
????????????W?=?2*random.random（size=shape）-1
????????????if?self.whiten?==?True:
????????????????W?=?self.orth（W）
????????????b?=?2*random.random（）-1
????????????yield?（Wb）
????
????def?generator_nodes（self?data?times?batchsize?nonlinear）:
????????self.Wlist?=?[elem[0]?for?elem?in?self.generator（（data.shape[1]batchsize）times）]
????????self.blist?=?[elem[1]?for?elem?in?self.generator（（data.shape[1]batchsize）times）]
????????
????????self.nonlinear?=?{‘linear‘:self.linear
??????????????????????????‘sigmoid‘:self.sigmoid
??????????????????????????‘tanh‘:self.tanh
??????????????????????????‘relu‘:self.relu
??????????????????????????}[nonlinear]
????????nodes?=?self.nonlinear（data.dot（self.Wlist[0]）+self.blist[0]）
????????for?i?in?range（1len（self.Wlist））:
????????????nodes?=?np.column_stack（（nodes?self.nonlinear（data.dot（self.Wlist[i]）+self.blist[i]）））
????????return?nodes
????????
????def?transform（selftestdata）:
????????testnodes?=?self.nonlinear（testdata.dot（self.Wlist[0]）+self.blist[0]）
????????for?i?in?range（1len（self.Wlist））:
????????????testnodes?=?np.column_stack（（testnodes?self.nonlinear（testdata.dot（self.Wlist[i]）+self.blist[i]）））
????????return?testnodes???

????def?update（selfotherW?otherb）:
????????self.Wlist?+=?otherW
????????self.blist?+=?otherb
????????
class?scaler:
????def?__init__（self）:
????????self._mean?=?0
????????self._std?=?0
????
????def?fit_transform（selftraindata）:
????????self._mean?=?traindata.mean（axis?=?0）
????????self._std?=?traindata.std（axis?=?0）
????????return?（traindata-self._mean）/self._std
????
????def?transform（selftestdata）:
????????return?（testdata-self._mean）/self.

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2018-06-19?10:37??Broad-Learning-System-master\
?????文件????????1203??2018-06-19?10:37??Broad-Learning-System-master\.gitignore
?????目錄???????????0??2018-06-19?10:37??Broad-Learning-System-master\BroadLearning\
?????文件????????6927??2018-06-19?10:37??Broad-Learning-System-master\BroadLearning\bls.py
?????文件???????11338??2018-06-19?10:37??Broad-Learning-System-master\BroadLearning\bls_addinput.py
?????文件????????8632??2018-06-19?10:37??Broad-Learning-System-master\BroadLearning\bls_enhence.py
?????文件????????9265??2018-06-19?10:37??Broad-Learning-System-master\BroadLearning\bls_enhmap.py
?????文件????????8465??2018-06-19?10:37??Broad-Learning-System-master\BroadLearning\bls_mapping.py
?????文件????????1073??2018-06-19?10:37??Broad-Learning-System-master\LICENSE
?????文件??????????33??2018-06-19?10:37??Broad-Learning-System-master\README.md