Unsupervised_Machine_Learning

Myopia Data Analysis

As a member of the Data Science Team at a prestigious medical research company, we are interested in finding better ways to predict Myopia (near-sightedness). My team has tried, unsuccessfully, to improve our classification model when training on the whole dataset. We believe there may be distinct groups of patients which need to be analyzed separately. Our supervisor has requested for my team to explore this option using unsupervised learning.

STEPS OF THE PROCESS

Part 1. Prepare the data.

Part 2. Apply Dimensionality Reduction.

Part 3. Perform a cluster analysis using K-Means.

Part 4. Make a recommendation based on the analysis.

FOR MORE INFORMATION ON MYOPIA AND TREATMENT OPTIONS VISIT THIS LINK TO THE MAYO CLINIC

https://www.mayoclinic.org/diseases-conditions/nearsightedness/symptoms-causes/syc-20375556