hanshupe
hanshupe
Is there any support for KDE (Kernel Density Estimation) based outlier detection planned?
In some cases transforming the target will improve the prediction drastically for regression problems (see: https://scikit-learn.org/stable/auto_examples/compose/plot_transformed_target.html) Can I use the sklearn.compose.TransformedTargetRegressor step in a tpot pipeline, so that it transforms...
In my pipeline I use the SelectFromModel step with a LinearRegression model for feature selection. It requires standardization of the input features using the StandardScaler. But I would like to...
Can I add a list for score_func, so that the optimal function is selected by tpot during the optimization? ``` 'sklearn.feature_selection.SelectKBest': { 'k': range(3, 20), 'score_func': [ 'sklearn.feature_selection.mutual_info_regression': None ,...
I wonder if there is an operator available to filter out rows from the training data based on tuneable parameters. I am only aware of the Selector-Transformer-Regressor steps, but I...
I see that after the TPOT optimization a preprocessor like robustScaler was selected. I wonder if it's possible that robustScaler is applied not on the entire set of features but...
Is it the following behaviour expected? I start tpot with a fixed template "Selector-Transformer-Regressor" but then I get a StackingEstimator model. I am not completely sure, but I think I...
Can the ASTRA framework also be used for multi-label classifications? As I understood weak supervisors are taking advantage of conflicting rules and labels, which would not work with multi-labels. Any...
Is there anything to consider for multi-labelling problems?
In the provided examples GPL us used for semantic search tasks: given a query, relevant results should be retrieved. Is it also the recommended approach to get meaningful embeddings /...