Machine Learning is used across many spheres around the world. The healthcare industry is no exception. Machine Learning can play an essential role in predicting presence/absence of Locomotor disorders, Heart diseases and more. Such information, if predicted well in advance, can provide important insights to doctors who can then adapt their diagnosis and treatment per patient basis.
In this particular project, I used Logistic Regression with 85% Accuracy. But In near future, Gonna add more classification algorithms to check their Accuracies.
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Logistic Regression:
Logistic regression is another powerful supervised ML algorithm used for binary classification problems (when target is categorical). The best way to think about logistic regression is that it is a linear regression but for classification problems. Logistic regression essentially uses a logistic function to model a binary output variable.
Data Source Link: https://drive.google.com/file/d/1Cxr9FzD7FGD5gaZvbxmDU8fYctK0Fx0N/view?usp=sharing
- Data Set Characteristics: Multivariate
- Number of Instances: 1025
- Area: Life / Healthcare
- Attribute Characteristics: Numbers
- Number of Attributes: 13
- Associated Tasks: Classification
- Missing Values? No