-
Notifications
You must be signed in to change notification settings - Fork 0
4 machine learning models applied to 2 seperate binary classification problems each. These models include decision trees, neural networks, random forest bagging, and k-nearest neighbor.
License
sully020/supervised_classification_ml
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
Instructions: 1.) Download and open main.py. 2.) Ensure the following libraries are installed: a.) pandas b.) numpy c.) sklearn 3.) Ensure that the emails.csv and diabetes.csv files are in the same folder as main.py. 4.) Run main.py, and input your choice of learner for each problem as they are typed out in the prompt. The code will report to you the mean test score, training score, and training time of the learners which you chose for each respective problem. Un-comment the calls to 'generate_data_heatmap()' in order to receive a visual representation of the confusion matrix for each specific learner.
About
4 machine learning models applied to 2 seperate binary classification problems each. These models include decision trees, neural networks, random forest bagging, and k-nearest neighbor.
Topics
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published