Test out various classification models like SVM, GaussianNB, K-Nearest etc.. on your dataset by applying various hyper parameters in real time & choose the best model for your data.
- Preprocess your dataset such that there are no missing values & no strings in the columns.
- Label the output vector column as Outcome .i.e.
| X1 | X2 | X3 | ... | Xn | Outcome |
|---|---|---|---|---|---|
| 0 | |||||
| 1 |
- Upload the dataset in CSV format.
- Choose the desired model from the side bar, Tweak the hyper parameters, Choose the matrix & click classify.
- Analyse the graphs, select the model with the highest accuracy & precision.
- Use the selected model to train your dataset in any app you are building as it will be the best fit for that particular dataset.