# Estimating Continuous Distributions in Bayesian Classifiers

arXiv: https://arxiv.org/abs/1302.4964 · HTML: https://mlsanity.com/paper/1302.4964/

## Key facts

- Cited by 54 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Feb 2013.

## Built on by (most cited first, 30 of 54)

- [BanglaBook: A Large-scale Bangla Dataset for Sentiment Analysis from Book Reviews](https://mlsanity.com/paper/2305.06595/) (2023)
- [VeriLA: A Human-Centered Evaluation Framework for Interpretable Verification of LLM Agent Failures](https://mlsanity.com/paper/2503.12651/) (2025)
- [Performance and accuracy assessments of an incompressible fluid solver coupled with a deep Convolutional Neural Network](https://mlsanity.com/paper/2109.09363/) (2021)
- [Enhancing Text Authenticity: A Novel Hybrid Approach for AI-Generated Text Detection](https://mlsanity.com/paper/2406.06558/) (2024)
- [GGNB: Graph-Based Gaussian Naive Bayes Intrusion Detection System for CAN Bus](https://mlsanity.com/paper/2108.10908/) (2021)
- [Semiparametric Bayesian Networks](https://mlsanity.com/paper/2109.03008/) (2021)
- [Product Progression: a machine learning approach to forecasting industrial upgrading](https://mlsanity.com/paper/2105.15018/) (2021)
- [Efficient Fraud Detection Using Deep Boosting Decision Trees](https://mlsanity.com/paper/2302.05918/) (2023)
- [Network Anomaly Detection for IoT Using Hyperdimensional Computing on NSL-KDD](https://mlsanity.com/paper/2503.03031/) (2025)
- [Efficient Intrusion Detection Using Evidence Theory](https://mlsanity.com/paper/2103.08585/) (2021)
- [Artificial Intelligence in Tumor Subregion Analysis Based on Medical Imaging: A Review](https://mlsanity.com/paper/2103.13588/) (2021)
- [CyberLearning: Effectiveness Analysis of Machine Learning Security Modeling to Detect Cyber-Anomalies and Multi-Attacks](https://mlsanity.com/paper/2104.08080/) (2021)
- [Planning for Manipulation among Movable Objects: Deciding Which Objects Go Where, in What Order, and How](https://mlsanity.com/paper/2303.13385/) (2023)
- [Online Learning under Haphazard Input Conditions: A Comprehensive Review and Analysis](https://mlsanity.com/paper/2404.04903/) (2024)
- [An Exploratory Deep Learning Approach for Predicting Subsequent Suicidal Acts in Chinese Psychological Support Hotlines](https://mlsanity.com/paper/2408.16463/) (2024)
- [Identify As A Human Does: A Pathfinder of Next-Generation Anti-Cheat Framework for First-Person Shooter Games](https://mlsanity.com/paper/2409.14830/) (2024)
- [On the efficacy of old features for the detection of new bots](https://mlsanity.com/paper/2506.19635/) (2025)
- [Domain Knowledge-Enhanced LLMs for Fraud and Concept Drift Detection](https://mlsanity.com/paper/2506.21443/) (2025)
- [Needmining: Designing Digital Support to Elicit Needs from Social Media](https://mlsanity.com/paper/2101.06146/) (2021)
- [A review of artificial intelligence methods combined with Raman spectroscopy to identify the composition of substances](https://mlsanity.com/paper/2104.04599/) (2021)
- [Using machine learning techniques to predict hospital admission at the emergency department](https://mlsanity.com/paper/2106.12921/) (2021)
- [Sampling Streaming Data with Parallel Vector Quantization -- PVQ](https://mlsanity.com/paper/2210.01792/) (2022)
- [Detecting Suicidality in Arabic Tweets Using Machine Learning and Deep Learning Techniques](https://mlsanity.com/paper/2309.00246/) (2023)
- [Maximizing Information Gain in Privacy-Aware Active Learning of Email Anomalies](https://mlsanity.com/paper/2405.07440/) (2024)
- [Classical Machine Learning: Seventy Years of Algorithmic Learning Evolution](https://mlsanity.com/paper/2408.01747/) (2024)
- [XNB: Explainable Class-Specific NaIve-Bayes Classifier](https://mlsanity.com/paper/2411.01203/) (2024)
- [Joint Detection of Fraud and Concept Drift inOnline Conversations with LLM-Assisted Judgment](https://mlsanity.com/paper/2505.07852/) (2025)
- [Proposal and study of statistical features for string similarity computation and classification](https://mlsanity.com/paper/2605.15110/) (2026)
- [The Semantic Adjacency Criterion in Time Intervals Mining](https://mlsanity.com/paper/2101.03842/) (2021)
- [Misinformation detection in Luganda-English code-mixed social media text](https://mlsanity.com/paper/2104.00124/) (2021)

## Abstract (arXiv)

When modeling a probability distribution with a Bayesian network, we are faced with the problem of how to handle continuous variables. Most previous work has either solved the problem by discretizing, or assumed that the data are generated by a single Gaussian. In this paper we abandon the normality assumption and instead use statistical methods for nonparametric density estimation. For a naive Bayesian classifier, we present experimental results on a variety of natural and artificial domains, comparing two methods of density estimation: assuming normality and modeling each conditional distribution with a single Gaussian; and using nonparametric kernel density estimation. We observe large reductions in error on several natural and artificial data sets, which suggests that kernel estimation is a useful tool for learning Bayesian models.