Write a paper on Interpret ability of Machine Learning models – Survey on various techniques and Metrics.Machine learning models are becoming more and more popular as they help various business-driven decisions. However, these models are a black box that is difficult to explain and has no clear understanding. As the usage of machine learning increases, there is an increased demand for the ability to understand, explain, analyze, and trust these models. Interpretability of a model has become crucial in this regard. Despite many interpretability models available, there is no consensus on which model is ideal and more helpful in understanding the results from a model. This paper will help us to compare and understand how each interpretability model works.
Example: https://www.twosigma.com/articles/interpretability-methods-in-machine-learning-a-brief-survey/
https://www.researchgate.net/publication/334717462_Machine_Learning_Interpretability_A_Survey_on_Methods_and_Metrics
Please explain the working of each technique. Include analysis and comparison of various techniques used for model interpretability by using a quality dataset for regression and classification models separately in python. Please reach out to me for more questions.
Please provide the python code used for each technique for regression and classification.
Please include tables for comparison of various techniques and images of each of the techniques used for analysis.
Please use at least 6 or 7 different techniques for model interpretability in Machine Learning for this research paper.
