Useful packages for predictions in machine learning

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

from  revolution analytics:

Ricky Ho has created a reference a 6-page PDF reference card on Big Data Machine Learning, with examples implemented in the R language. (A free registration to DZone Refcardz is required to download the PDF.) The examples cover:

• Predictive modeling overview (how to set up test and training sets in R)
• Linear regression (using lm)
• Logistic regression (using glm)
• Regression with regularization (using the glmnet package)
• Neural networks (using nnet)
• Support vector machines (using tune.svm from the e1071 package)
• Naïve Bayes models (using naiveBayes from the e1071 package)
• K-nearest-neighbors classification (using the knn function from the class package)
• Decision trees (using rpart)
• Ensembles of trees (using the randomForest package)
• Gradient boosting (using the gbm package)
  

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏2 回帖

关键词：Predictions Prediction Packages Learning earning overview download test revolution reference