In this section, we will predict breast cancer using PCA and PCR analysis.
📌 Breast cancer is the most common cancer amongst women in the world. It accounts for 25% of all cancer cases, and affected over 2.1 Million people in 2015 alone. It starts when cells in the breast begin to grow out of control. These cells usually form tumors that can be seen via X-ray or felt as lumps in the breast area.
📌 The key challenge against its detection is how to classify tumors into malignant (cancerous) or benign(noncancerous). We ask you to complete the analysis of classifying these tumors using machine learning and the Breast Cancer Wisconsin (Diagnostic) Dataset.
📌 This dataset of breast cancer patients was obtained from the 2017 November update of the SEER Program of the NCI, which provides information on population-based cancer statistics. The dataset involved female patients with infiltrating duct and lobular carcinoma breast cancer (SEER primary cites recode NOS histology codes 8522/3) diagnosed in 2006-2010. Patients with unknown tumour size, examined regional LNs, positive regional LNs, and patients whose survival months were less than 1 month were excluded; thus, 4024 patients were ultimately included.