/Machine-Learning-Algorithms

Conventional Algorithms in Machine Learning.

Primary LanguageJupyter NotebookMIT LicenseMIT

Machine-Learning-Algorithms

This repository consists of some Conventional Machine Learning Algorithms. I used Social Network Ads Dataset for comparision between algorithms.

Data Visualization

20210409_194236.gif

Algorithms

Final Prediction Boundraries of each algorithm is shown bellow.

Linear Regression

lin1 lin2

Logistic Regression

log1 log2

SVM

Kernel Used: RBF

svm1 svm2

Decision Tree

Some more Visualization for Decision Tree:

20210409_225232.gif

dt3 dt4

Naive Bayes

nb1 nb2

KNN

k1 k2

Comparing Accuracys & Errors in Different Algorithms

It includes (for both train set and test test:
* Confusion Matrix
* Accuracy
* Mean Absolute Error
* Mean Squared Error
* Root Mean Sqaure Error
* Precision
* Recall
* F-Score
  • For Training Data:

WhatsApp Image 2021-03-24 at 11 44 32 PM

  • For Testing Data:

WhatsApp Image 2021-03-24 at 11 44 32 PM (1)

Dependencies

* Python: 3.7.10
* Numpy: 1.19.5
* Pandas: 1.1.5
* Matplotlib: 3.2.2
* Seaborn: 0.11.1
* Bokeh: 2.3.0
* Sklearn: 0.22.2.post1

License

It is provided with MIT License.