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探索核函数在不同数据集上的表现 导入模块 import numpy as np import matplotlib.pyplot as plt from matplotlib.colors import ListedColormap from sklearn import svm from skle 阅读全文
posted @ 2023-04-24 21:22
ThankCAT
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线性 SVM 决策过程的可视化 导入模块 from sklearn.datasets import make_blobs from sklearn.svm import SVC import matplotlib.pyplot as plt import numpy as np 实例化数据集，可视化 阅读全文
posted @ 2023-04-23 22:40
ThankCAT
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from sklearn.datasets import make_blobs import matplotlib.pyplot as plt x, y = make_blobs(n_samples=500, n_features=2, centers=4, random_state=1) colo 阅读全文
posted @ 2023-04-21 00:45
ThankCAT
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评分卡案例 数据预处理 %matplotlib inline # 导入库 import pandas as pd import numpy as np from sklearn.linear_model import LogisticRegression as LR # 加载数据 data = pd 阅读全文
posted @ 2023-04-17 16:43
ThankCAT
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from sklearn.datasets import load_breast_cancer from sklearn.feature_selection import SelectFromModel from sklearn.linear_model import LogisticRegress 阅读全文
posted @ 2023-04-12 16:59
ThankCAT
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from sklearn.neighbors import KNeighborsClassifier as KNN from sklearn.decomposition import PCA from sklearn.ensemble import RandomForestClassifier as 阅读全文
posted @ 2023-04-10 22:12
ThankCAT
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import pandas as pd import numpy as np import matplotlib.pyplot as plt # 准备数据 data = pd.read_csv("./digit recognizor.csv") x = data.iloc[:,1:] # 特征矩阵 阅读全文
posted @ 2023-04-08 21:08
ThankCAT
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import pandas as pd data = pd.read_csv("./digit recognizor.csv") x = data.iloc[:,1:] y = data.iloc[:,0] x.shape (42000, 784) 方差过滤 VarianceThreshold fr 阅读全文
posted @ 2023-04-08 21:07
ThankCAT
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二值化与分段 sklearn.preprocessing.Binarizer from sklearn.preprocessing import Binarizer import pandas as pd data = pd.read_csv("./data_full", index_col=0) 阅读全文
posted @ 2023-04-08 21:07
ThankCAT
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处理缺失值 import pandas as pd import numpy as np df = pd.read_csv("./Narrativedata.csv", index_col=0) df.info() <class 'pandas.core.frame.DataFrame'> Int6 阅读全文
posted @ 2023-04-08 21:06
ThankCAT
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