ml机器学习算法的相关内容

【ML】关于机器学习中AdaBoost算法的学习

AdBoost介绍AdaBoost分类器就是一种元算法分类器，AdaBoost分类器利用同一种基分类器（弱分类器），基于分类器的错误率分配不同的权重参数，最后累加加权的预测结果作为输出。1、 Bagging方法在介绍AdaBoost之前，我们首先大致介绍一种基于数据随机重抽样的分类器构建方法，即ba...

ML之回归预测：利用十类机器学习算法(线性回归、kNN、SVM、决策树、随机森林、极端随机树、SGD、提升树、LightGBM、XGBoost)对波士顿数据集回归预测(模型评估、推理并导到csv)

目录利用十类机器学习算法(线性回归、kNN、SVM、决策树、随机森林、极端随机树、SGD、提升树、LightGBM、XGBoost)对波士顿数据集【13+1,506】回归预测(模型评估、推理并导到csv)输出数据集1、LiR 线性回归算法2、kNNR k最近邻算法3、SVMR 支持向量机算法4、DT...

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ML之分类预测：以六类机器学习算法(kNN、逻辑回归、SVM、决策树、随机森林、提升树、神经网络)对糖尿病数据集(8→1)实现二分类模型评估案例来理解和认知机器学习分类预测的模板流程

目录六类机器学习算法(kNN、逻辑回归、SVM、决策树、随机森林、提升树、神经网络)对糖尿病数据集(8→1)实现二分类预测数据集理解1、kNN2、逻辑回归3、SVM4、决策树5、随机森林6、提升树7、神经网络相关文章ML之分类预测：以六类机器学习算法(kNN、逻辑回归、SVM、决策树、随...

ML之回归预测：利用两种机器学习算法(LiR，XGBoost(调优+重要性可视化+特征选择模型))对无人驾驶汽车系统参数(2017年的data,18+2)进行回归预测值VS真实值

输出结果1、LiR模型LiR：The value of default measurement of LiR is 0.8729775261968014LiR：R-squared value of DecisionTreeRegressor: 0.87297752619680142、XGBoost模...

ML之回归预测：利用十(xgboost,10-1)种机器学习算法对无人驾驶汽车系统参数(2017年的data,18+2)进行回归预测值VS真实值——bug调试记录

输出结果1、增加XGBR算法1、增加XGBR算法时候，采用网格搜索的方法XGBR_grid_model Training time： 135.60037931849538输出XGBR_grid_model模型的最优参数： {'learning_rate': 0.03, 'max_depth': 4,...

ML之ECS：利用ECS的PAI进行傻瓜式操作机器学习的算法

ECS的PAI的简介阿里云机器学习是基于阿里云分布式计算引擎的一款机器学习算法平台，以极低的代价帮助您的业务从BI时代跨入AI时代，真正实现人工智能触手可及。算法丰富：100余种算法组件，覆盖回归、分类、聚类、文本分析等算法。深度学习（GPU...

ML之分类预测：基于sklearn库的七八种机器学习算法利用糖尿病(diabetes)数据集(8→1)实现二分类预测（二）

8、NN利用多层神经网络NN：Data standardization—Accuracy on training set: 0.823NN：Data standardization—Accuracy on test set: 0.802NN：Data standardization(max_iter...

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更新时间 2024-04-22 12:15:09

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