Cost optimization using normal linear regression method for breast cancer Type I skin

There are six main categories of breast cancer be existent. In this paper, we have taken the Type 1 carcinoma cancer to support the decision making. For this, a novel machine learning based cost optimization is applied to make an efficient decision from the samples. Moreover, we have applied our methodology on the real datasets to predict cancer with appropriate parameters using Pearson correlation. This work can be used well on lightweight devices like smartphones or tablets to decide more precisely with primary factors.