PRESISTANT: Learning based assistant for data pre-processing

TL;DR

PRESISTANT is a learning-based assistant that recommends data pre-processing operators to non-experts by predicting their impact on classification performance, thereby improving analysis outcomes.

Contribution

This work introduces PRESISTANT, a tool using Random Forests to rank pre-processing operators based on their effect on classifier accuracy, aiding non-expert users.

Findings

PRESISTANT effectively improves classification accuracy for non-expert users.

The tool successfully predicts the impact of pre-processing operators across multiple classifiers.

Extensive evaluations demonstrate the usefulness of PRESISTANT in real-world scenarios.

Abstract

Data pre-processing is one of the most time consuming and relevant steps in a data analysis process (e.g., classification task). A given data pre-processing operator (e.g., transformation) can have positive, negative or zero impact on the final result of the analysis. Expert users have the required knowledge to find the right pre-processing operators. However, when it comes to non-experts, they are overwhelmed by the amount of pre-processing operators and it is challenging for them to find operators that would positively impact their analysis (e.g., increase the predictive accuracy of a classifier). Existing solutions either assume that users have expert knowledge, or they recommend pre-processing operators that are only "syntactically" applicable to a dataset, without taking into account their impact on the final analysis. In this work, we aim at providing assistance to non-expert users by recommending data pre-processing operators that are ranked according to their impact on the final analysis. We developed a tool PRESISTANT, that uses Random Forests to learn the impact of pre-processing operators on the performance (e.g., predictive accuracy) of 5 different classification algorithms, such as J48, Naive Bayes, PART, Logistic Regression, and Nearest Neighbor. Extensive evaluations on the recommendations provided by our tool, show that PRESISTANT can effectively help non-experts in order to achieve improved results in their analytical tasks.