Supervised Learning: Logistic Regression | Evaluation of Classification Model | Day (5/45) | A2Z ML | Mohd Saqib

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In this blog, we will discussed about logistic regression and and evaluation technique of classification models in detail.

Day 5

Imagine you’re a farmer who has a large apple orchard. You’ve noticed that some of the apples on your trees are turning red, while others are still green. You want to predict which apples will turn red so you can harvest them at the right time. You decide to gather data on the apples, such as their size, shape, and location on the tree. You notice that the apples that are located in areas with more sunlight are more likely to turn red. You decide to use this data to build a model that can predict which apples will turn red. You realize that logistic regression is the perfect algorithm for this task because it can model the probability of an event occurring based on input features. With the help of logistic regression, you’re able to harvest all the red apples at the right time and increase your profits.

Index
1. Logistic Regression

• Definition and mathematical formulation
• Coding implementation in Python