Prediction Operators
Prediction (Predict) operators are used to apply a particular modeling algorithm operator to a new dataset for prediction purposes.
- Chi Square, Goodness of Fit
Computes a Pearson's Chi Square test for goodness of fit of a distribution. - Chi Square, Independence Test
Determines whether categorical columns are statistically independent of a categorical dependent variable column. - Classifier (DB)
Uses any input classification model to apply a classification prediction to the input data set. - Classifier (HD)
Uses any input classification model to apply a classification prediction to the input data set. - Collaborative Filter Predictor
Outputs predicted ratings for products using the Collaborative Filtering model created by the trainer. Uses both the model trained by the Collaborative Filter Trainer and a data set. - Collaborative Filter Recommender
Using the model trained by the Collaborative Filter Trainer, outputs recommendations for those users or products. - K-Means Predictor - MADlib
The k-means predictor (MADlib) operator output is simply the assignment of the input data members to the k number of clusters, the centroids already predetermined by the K-means (MADlib) operator. - PCA Apply
Uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of uncorrelated variables (principal components). - Predictor (DB)
Applies an input regression, classification, or clustering model to an input data set in order to predict a value (or the highest probability value) - Predictor (HD)
Applies an input regression, classification, or clustering model to an input dataset in order to predict a value (or the highest probability value).
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