Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Natnael-Bacha/icog-labs-naive-bayes-implementation

Domaine:

natural language processing

Type de record:

software
Créateur:
Nat
Hôte:
"# icog-labs-naive-bayes-implementation" # Customer Support Ticket Router A customer-support intent classification system built from scratch using **Multinomial Naive Bayes and NumPy**. The system takes a customer's message and predicts the most appropriate support intent, such as `cancel_order`, `track_order`, `payment_issue`, `recover_password`, `change_order`, `check_invoice`, and `get_refund`. The project also includes a Tkinter GUI for testing individual customer requests and an evaluation system for measuring model performance. --- ## Features * Multinomial Naive Bayes classifier implemented from scratch * NumPy-based model calculations * Text preprocessing * Unigram and bigram features * Stopword removal * Document-frequency based vocabulary filtering * Laplace smoothing * Stratified train/test splitting * Accuracy, Precision, Recall, and F1 evaluation * Classification report * Error analysis * Tkinter graphical interface * No machine-learning library is used for the classifier --- ## Dataset This project uses the **Bitext Customer Support Training Dataset**, specifically: `Bitext_Sample_Customer_Support_Training_Dataset_27K_responses-v11` Credit goes to the dataset creators for providing the customer-support training data used in this project. After duplicate removal, the dataset contained: Original records: 26,872 Duplicates removed: 2,237 Remaining records: 24,635 The dataset contains customer-support intents covering areas such as: * Order cancellation * Order changes * Shipping address changes * Payment issues * Payment methods * Invoice requests * Refunds * Account creation * Account deletion * Password recovery * Delivery information * Order tracking * Customer service * Complaints * Reviews * Newsletter subscriptions ## Technologies * **Python** * **NumPy** — model calculations and numerical operations * **Pandas** — dataset handling * **Tkinter** — graphical user interface --- ## Project Structure ```text customerSupp …

Visit

github.com

Tasks

text classification

Languages

Kwegu

Similaires

rebiraolin/amharic-naive-bayesEmmanuellaBudu/Bantu-Language-Classifier-with-Naive-BayesHypertension Prediction System Using Naive Bayes ClassifierApplication of Naive Bayes to Students’ Performance ClassificationAndroid Based Naive Bayes Probabilistic Detection Model for Breast Cancer and Mobile Cloud Computing: Design and ImplementationKLASIFIKASI TINGKAT TUTUR BAHASA SASAK BERBASIS TEKS MENGGUNAKAN NAIVE BAYES

rebiraolin/amharic-naive-bayes

# Naive Bayes from First Principles: Amharic News Topic Classification A **from-scratch Multinomial

EmmanuellaBudu/Bantu-Language-Classifier-with-Naive-Bayes

A simple Naive Bayes Classifier to classify Bantu languages (Setswana and Sesotho) # Bantu-Language

Hypertension Prediction System Using Naive Bayes Classifier

International audience Hypertension is an illness that often leads to severe and life

Application of Naive Bayes to Students’ Performance Classification

International audience Naive Bayes Classifier is a strong tool or model in classifyin

Android Based Naive Bayes Probabilistic Detection Model for Breast Cancer and Mobile Cloud Computing: Design and Implementation

Mobile phone technology initiatives are revolutionizing healthcare delivery in Africa and other deve

KLASIFIKASI TINGKAT TUTUR BAHASA SASAK BERBASIS TEKS MENGGUNAKAN NAIVE BAYES

Abstrak. Tujuan dari penelitian ini adalah untuk menilai efektivitas klasifikasi tingkat tutur bahas