In this Persian tutorial, we work on the prostate cancer dataset and run a simple linear regression model on it. The data for this example come from a study by Stamey et al. (1989). They examined the correlation between the level of prostate-specific antigen and a number of clinical measures in men who were about to receive a radical prostatectomy. The variables are log cancer volume (lcavol), log prostate weight (lweight), age, log of the amount of benign prostatic hyperplasia (lbph), seminal vesicle invasion (svi), log of capsular penetration (lcp), Gleason score (Gleason), and percent of Gleason score 4 or 5 (pgg45).
This video has been uploaded to both YouTube and Aparat.
Reference book: The Elements of Statistical Learning: Data Mining, Inference, and Prediction.
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