From 5600fcd8462f827f6283681723ee5a26d5e7ca06 Mon Sep 17 00:00:00 2001 From: JiaYanhao <2474840061@qq.com> Date: Sat, 23 Jul 2022 16:53:46 +0800 Subject: [PATCH] 0.0.4 --- .DS_Store | Bin 6148 -> 6148 bytes BaseML/.DS_Store | Bin 0 -> 6148 bytes BaseML/GaussianNB.py | 4 ++-- BaseML/{KNN.py => KNNClassifier.py} | 0 BaseML/PCA.py | 10 +++++----- BaseML/Perceptron.py | 4 ++-- BaseML/__init__.py | 17 +++++++++++++++++ 7 files changed, 26 insertions(+), 9 deletions(-) create mode 100644 BaseML/.DS_Store rename BaseML/{KNN.py => KNNClassifier.py} (100%) create mode 100644 BaseML/__init__.py diff --git a/.DS_Store b/.DS_Store index 603d9d9c6a88b4b3cf3d1cf39dc66499c2dba59c..4f6eca85f315c7d32a2829bdba8825a3633267cf 100644 GIT binary patch delta 493 zcmZoMXfc=|#>B!kF;Q%yo+2a9#DLw4n3x%PCi5^>*K;$(17RjZ9uSv+*?J5G43(Za z`N>H+`AG~63<5yx2*i5-!2rl&U|?f#Vn}2tW=Li5W$-~$yAddFfJ<#sd2s>M+#N{; zIhpmvB?bo97@3$^SlQS)*g3d4VuLgC%Y#c2OG=BK5{sfiypa6-oFo`KF)1uFwLD%x z#5q5&Br!8DwFs;sGbI(MBqlsFFD1X+DZex?r5LO?7$U*J$-x;fAW>ayYG9zFU}9!c ztD{hDX=G3jd!<{sgJre21}-aWgvyKL;=p eH-BXO&ODi4#8Log6WD=3f(fXMVRMAY8fE}`etiP~ delta 78 zcmZoMXfc=|#>B`mF;Q%yo+2aL#DLw5Y?FCdswcCvC2SVs5M*L#6K7iVu(r%7`MtxB_TjS7VKv4KllrNpDR7Lt;x(# zw?@sqliSnj+|%2h$+S}drnQ}%0(Aftx?u5$MZn~__?{JfOObs`Si%=FLqfgJi#4+FEDi|wcPsj3B?T;(KJzK0IYk-<6pbDr0X$53`i0Fc` z$HbvsI#}2v0I|qsYpl!9f^Z^_vB$(ApU{k>5*^j}BZhHwwnsiL_Lw+ybQpj5Fg~;K zClq6|v;WA3!^94?R0ULltO5t_wl4dB=lk=2mZW#8fGY5>6fnj1pxxq>{NB1ZIoWF? s`aNAt;u43J!oqLIwjx{cG2I%UMN%Qg9utRbq3Mr+l|c(t;71ks1g`y}t^fc4 literal 0 HcmV?d00001 diff --git a/BaseML/GaussianNB.py b/BaseML/GaussianNB.py index 0b281ea..403adb7 100644 --- a/BaseML/GaussianNB.py +++ b/BaseML/GaussianNB.py @@ -3,7 +3,7 @@ import os from sklearn.metrics import accuracy_score, mean_squared_error -from sklearn.naive_bayes import GaussianNB +from sklearn.naive_bayes import GaussianNB as gauss class GaussianNB: @@ -11,7 +11,7 @@ def __init__(self ): self.cwd = os.path.dirname(os.getcwd()) # 获取当前文件的绝对路径 self.file_dirname = os.path.dirname(os.path.abspath(__file__)) - self.model = GaussianNB() + self.model = gauss() self.dataset_path = ' ' self.test_size = ' ' self.test_set = ' ' diff --git a/BaseML/KNN.py b/BaseML/KNNClassifier.py similarity index 100% rename from BaseML/KNN.py rename to BaseML/KNNClassifier.py diff --git a/BaseML/PCA.py b/BaseML/PCA.py index 2d685ed..de7e91c 100644 --- a/BaseML/PCA.py +++ b/BaseML/PCA.py @@ -1,4 +1,4 @@ -from sklearn.decomposition import PCA +from sklearn.decomposition import PCA as pca_reduction import os @@ -10,9 +10,9 @@ def __init__(self, self.cwd = os.path.dirname(os.getcwd()) # 获取当前文件的绝对路径 self.file_dirname = os.path.dirname(os.path.abspath(__file__)) - self.dataset = '' - self.x_train, self.x_test = 0, 0 - self.model = PCA(n_components=n_components) + self.dataset = None + # self.x_train, self.x_test = 0, 0 + self.model = pca_reduction(n_components=n_components) def train(self): self.model.fit(self.dataset) @@ -20,7 +20,7 @@ def train(self): # 返回所保留的n个成分各自的方差百分比,这里可以理解为单个变量方差贡献率。 def inference(self, data): - self.model.fit_transform(data) + self.model.transform(data) print(self.model.n_features_) print(self.model.n_samples_) diff --git a/BaseML/Perceptron.py b/BaseML/Perceptron.py index 88472bf..8a094df 100644 --- a/BaseML/Perceptron.py +++ b/BaseML/Perceptron.py @@ -1,4 +1,4 @@ -from sklearn.linear_model import Perceptron +from sklearn.linear_model import Perceptron as per import os @@ -11,7 +11,7 @@ def __init__(self self.file_dirname = os.path.dirname(os.path.abspath(__file__)) self.dataset = '' self.x_train, self.x_test = 0, 0 - self.model = Perceptron() + self.model = per() def train(self): self.model.fit(self.dataset) diff --git a/BaseML/__init__.py b/BaseML/__init__.py new file mode 100644 index 0000000..412a05e --- /dev/null +++ b/BaseML/__init__.py @@ -0,0 +1,17 @@ +from .CART import CART +from .KNNClassifier import KNN +from .PCA import PCA +from .Perceptron import Perceptron +from .AdaBoost import AdaBoost +from .GaussianNB import GaussianNB +from .SVM import SVM + + +__all__ = [ + 'CART', + 'SVM', + 'AdaBoost', + 'GaussianNB', + 'KNN', + 'PCA', + 'Perceptron']