IBM_Machine_Learning_With_Python 源码
v 回归 油耗的简单,多元和多项式回归 对汽车的油耗和二氧化碳排放量实施简单,多项式和多项式线性回归; 将油耗数据分为训练集和测试集,使用训练集创建模型; 通过包括平均绝对误差(MAE),残差平方和(MSE)和R2分数在内的度量标准,使用测试集评估模型; 最后预测未知值 viz = df[['ENGINESIZE','CYLINDERS','FUELCONSUMPTION_COMB','CO2EMISSIONS']] viz.head(10) plt.scatter(viz.ENGINESIZE,viz.CO2EMISSIONS, color = 'skyblue') plt.xlabel("
文件列表
IBM_Machine_Learning_With_Python-master.zip
(预估有个8文件)
IBM_Machine_Learning_With_Python-master
KNN on Telecommunications Customer Classification.ipynb
34KB
SVM on Cancer Classification.ipynb
58KB
Hierarchical Clustering on Car Model.ipynb
561KB
Logistic Regression on Customer Churn.ipynb
49KB
Simple & Multiple & Polynomial Regressions on Fuel Consumption.ipynb
165KB
README.md
3KB
K-Means Clustering on Customer Segementation.ipynb
388KB
Decision Trees on Patients'Drug Classification.ipynb
397KB
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