To get predictions from trained models you can download model in
Deploy view or you can upload test dataset into MLJAR and use it for prediction. This situation is described below.
- Upload you data file in
- Accept attributes usage in
Previewfor uploaded dataset.
- Go to
Predictview, in top right corner select dataset which will be used for prediction.
- Select algorithm that will be used, by selecting checkbox.
Start Predictionand wait a while. Click
Refreshon the bottom of the page to see if prediction is computed.
- Your predictions will be displayed in the bottom of the page where you can download it.
In case of training with cross-validation (CV) all models computed during CV will be used for prediction and their predictions will be averaged. For example, if you run algorithm training with 5 fold CV, then for each parameter setting you have 5 models trained on different train folds. For computing a prediction on new dataset, there will be computed 5 predictions from each model and averaged - this is what you download.
In case of training with separate validation dataset, there is only one model trained and only one model is used for computing predictions.