KNN_Cancer_predict（癌症预测）

KNN_Cancer_predict（癌症预测）import numpy as np

import pandas as pd

from pandas import Series,DataFrame

ighbors import KNeighborsClassifier

cancer = pd.read_csv('./data/cancer.csv',sep='\t')

print(cancer.shape)

cancer

是什么让你如此美丽#target中m恶性，b良性

qiushi

data = cancer.iloc[:,2:]

target = cancer.iloc[:,1]

display(data.head(),target.head())

knn = KNeighborsClassifier(n_neighbors=15)

#打乱顺序，并且给它⼀分为⼆，训练数据，预测数据

#sklearn为我们能提供⽅法

del_selection import train_test_split王绪恭

#使⽤其进⾏分割

X_train,X_test,y_train,y_test = train_test_split(data,target,test_size = 0.1)

knn.fit(X_train,y_train)

KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',

metric_params=None, n_jobs=1, n_neighbors=15, p=2,

weights='uniform')

score = knn.score(X_test,y_test)

y_ = knn.predict(X_test)

print(score)

0.9473684210526315

#可以说明真实值和预测值拿⼀些数据不同了

长丰cs7

#提升准确度

#对数据进⾏清洗

data

#归⼀化

苯甲酸苄酯#(num -min)/(max-min)

columns = lumns

for col in columns:

data_min = data[col].min()

data_max = data[col].max()

# data[col] = (data[col] -data_min)/(data_max-data_min)

print(data[col])

微电影青春期break;

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标签：数据预测训练良性顺序提升恶性打乱

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