based on the https://github.com/mljar/mljar-supervised
If someone is looking for ready to use, easy to install( here on lubuntu) automatised ml package for analysis of tabular data
this is really excellent choice.
I am really impressed by way of presenting and storage results by mentioned package.
To check and play input data with Moskow flat prices were used.
Typical example for regresion to evaluate the price
metric mae.
Best model | name | model_type | metric_type | metric_value | train_time |
---|---|---|---|---|---|
1_Baseline | Baseline | mae | 0.225592 | 2.68 | |
2_DecisionTree | Decision Tree | mae | 0.186864 | 21.44 | |
the best | 3_Default_Xgboost | Xgboost | mae | 0.111216 | 29.3 |
4_Default_NeuralNetwork | Neural Network | mae | 0.136117 | 9.68 | |
5_Default_RandomForest | Random Forest | mae | 0.16243 | 39.82 | |
Ensemble | Ensemble | mae | 0.111216 | 1.53 |