Commit de2814b

author

codebasics

committed

pca

1 parent 5aab293 commit de2814bCopy full SHA for de2814b

File tree

-2

lines changed

-2

lines changed

Lines changed: 2 additions & 2 deletions

Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-Download heart disease dataset heart.csv in Exercise folder and do following, (credits of dataset: https://www.kaggle.com/fedesoriano/heart-failure-prediction)`
	`1`	`+Download heart disease dataset heart.csv in [Exercise](https://github.com/codebasics/py/tree/master/ML/18_PCA/Exercise) folder and do following, (credits of dataset: https://www.kaggle.com/fedesoriano/heart-failure-prediction)`
`2`	`2`
`3`	`3`	`1. Load heart disease dataset in pandas dataframe`
`4`	`4`	`1. Remove outliers using Z score. Usual guideline is to remove anything that has Z score > 3 formula or Z score < -3`
`@@ -8,7 +8,7 @@ Download heart disease dataset heart.csv in Exercise folder and do following, (c`
`8`	`8`	`1. Now use PCA to reduce dimensions, retrain your model and see what impact it has on your model in terms of accuracy. Keep in mind that many times doing PCA reduces the accuracy but computation is much lighter and that's the trade off you need to consider while building models in real life`
`9`	`9`
`10`	`10`
`11`		`-[Solution Link]()`
	`11`	`+[Solution Link](https://github.com/codebasics/py/blob/master/ML/18_PCA/Exercise/PCA_heart_disease_prediction_exercise_solution.ipynb)`
`12`	`12`
`13`	`13`
`14`	`14`

Comments

(0)