Commit6d4492d

minjk-bl

committed

Add top count option for Plot_Feature_importances

1 parent7f771e0 commit6d4492dCopy full SHA for 6d4492d

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+11

-5

lines changed

+11

-5

lines changed

Lines changed: 3 additions & 2 deletions

Original file line number	Diff line number	Diff line change
`@@ -425,11 +425,12 @@ define([`
`425`	`425`	`'plot_feature_importances':{`
`426`	`426`	`name:'plot_feature_importances',`
`427`	`427`	`label:'Plot feature importances',`
`428`		`-code:"vp_plot_feature_importances(${model}, ${fi_featureData}${sort})",`
	`428`	`+code:"vp_plot_feature_importances(${model}, ${fi_featureData}${sort}${top_count})",`
`429`	`429`	`description:'Draw feature_importances_',`
`430`	`430`	`options:[`
`431`	`431`	`{name:'fi_featureData',label:'Feature Data',component:['data_select'],var_type:['DataFrame','Series','ndarray','list','dict'],value:'X_train'},`
`432`		`-{name:'sort',label:'Sort data',component:['bool_checkbox'],value:true,usePair:true}`
	`432`	`+{name:'sort',label:'Sort data',component:['bool_checkbox'],value:true,usePair:true},`
	`433`	`+{name:'top_count',label:'Top count',component:['input_number'],min:0,max:5,usePair:true},`
`433`	`434`	`]`
`434`	`435`	`}`
`435`	`436`	`}`

Lines changed: 8 additions & 3 deletions

Original file line number	Diff line number	Diff line change
`@@ -81,11 +81,16 @@ def vp_create_feature_importances(model, X_train=None, sort=False):`
`81`	`81`	`######`
`82`	`82`	`# Visual Python: Machine Learning > Model Info`
`83`	`83`	`######`
`84`		`-defvp_plot_feature_importances(model,X_train=None,sort=False):`
	`84`	`+defvp_plot_feature_importances(model,X_train=None,sort=False,top_count=0):`
`85`	`85`	`df_i=vp_create_feature_importances(model,X_train,sort)`
`86`	`86`
`87`		`-ifsort:df_i['Percentage'].sort_values().plot(kind='barh')`
`88`		`-else:df_i['Percentage'].plot(kind='barh')`
	`87`	`+ifsort:`
	`88`	`+iftop_count>0:`
	`89`	`+df_i['Percentage'].sort_values().tail(top_count).plot(kind='barh')`
	`90`	`+else:`
	`91`	`+df_i['Percentage'].sort_values().plot(kind='barh')`
	`92`	`+else:`
	`93`	`+df_i['Percentage'].plot(kind='barh')`
`89`	`94`	`_vp_plt.xlabel('Feature importance Percentage')`
`90`	`95`	`_vp_plt.ylabel('Features')`
`91`	`96`

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