{"id":5916,"date":"2015-07-30T13:30:17","date_gmt":"2015-07-30T17:30:17","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=5916"},"modified":"2017-08-03T12:11:01","modified_gmt":"2017-08-03T16:11:01","slug":"the-key-to-modelling-success-part0730151","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/the-key-to-modelling-success-part0730151\/5916\/","title":{"rendered":"The Key to Modelling Success-The Variable Selection Process (Part 2)"},"content":{"rendered":"Last month, I discussed the importance of variable selection as a key component of the modelling process. We examined three techniques: factor analysis, correlation analysis, and clustering. This month, we will explore CHAID\/Decision Tree, Exploratory Data Analysis(EDA), and Stepwise Regression as other techniques in selecting the appropriate variables for a given model. EDA presents a more visual rather than statistical perspective of how a given input variable impacts the target variable. EDA reports depict how a given input variable is trending against the target variable. The practitioner can then select those variables which visually exhibit a trend and <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/the-key-to-modelling-success-part0730151\/5916\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Last month, I discussed the importance of variable selection as a key component of the modelling process. We examined three techniques: factor analysis, correlation analysis, and clustering. This month, we will explore CHAID\/Decision Tree, Exploratory Data Analysis(EDA), and Stepwise Regression as other techniques in selecting the appropriate variables for a given model. EDA presents a [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[3],"tags":[486,485],"class_list":["post-5916","post","type-post","status-publish","format-standard","hentry","category-leading-stories","tag-boire-filler-group","tag-modelling"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5916","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=5916"}],"version-history":[{"count":4,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5916\/revisions"}],"predecessor-version":[{"id":8861,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/5916\/revisions\/8861"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=5916"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=5916"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=5916"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}