GitHub topics: logistic-regression-algorithm

Repositories

kennethleungty/Logistic-Regression-Assumptions

Assumptions of Logistic Regression, Clearly Explained

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kartikey2807/Bike-Classification-1RT700

Plotting trends, correlations and outliers in the feature space; classifying 'bike demand' for weather data, using regression and feature expansion.

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Abhi3886/LoanApprovalAnalysis

Loan Approval Analysis involves building a machine learning model to predict whether a loan will be approved or not based on various customer features

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Rudra-G-23/breast-cancer-prediction-app

A Streamlit web application for breast cancer prediction using logistic regression. Users can input key tumor features to receive real-time prediction and confidence scores based on the Breast Cancer Wisconsin Diagnostic Dataset.

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mehmoodulhaq570/Machine-Learning-Models

A repository consisting of machine learning models for predicting the future instance. More specifically this repository is a Machine Learning course for those who are interested in learning the basics of machine learning algorithms.

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MaklonFR/PredictiveAnalytics-StudentsPerformance

Submission Dicoding Indonesia - Machine Learning Terapan (Predictive Students Analytics)

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Tolumie/Loan-Approval-Prediction

Loan Approval Prediction using Machine Learning | EDA + Decision Tree, Random Forest & Logistic Regression | Automating loan eligibility for Dream Housing Finance by analyzing customer data and predicting loan approvals.

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ikanurfitriani/Diabetes-Prediction

This repository contains code archives for Diabetes Prediction with Machine Learning

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coding-ai/machine_learning_cpp

Machine Learning C++

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RamishFatimaa/OpticalDiseases

An AI-driven approach to predicting ocular diseases using machine learning and NLP for personalized patient treatment.

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gaball1/Alzheimer-Prediction-AI

Alzheimer Prediction is a machine learning-based project designed to predict the likelihood of Alzheimer’s disease using clinical and imaging data. The project features an interactive web application built with Streamlit, enabling users to input key data, view predictions, and explore visualizations .

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PatilNi3/PROJECT_MACHINE_LEARNING

Fake Currency Detection using Logistic Regression Algorithm

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ozlemkorpe/Data-Mining-With-Knime

Basic knime examples for beginners. It includes many different operations like filtering, predicting, string manipulation, math operations etc.

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ApoorvRusia/Logistic-Regression-Classifier-On-Social-Network-Advertising

This project is to work on basic dataset to use logistic regression algorithm to classify which customer is going to buy the product.

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Tanmayee2010/Heart-Attack-Prediction

Heart Attack Prediction Using Machine Learning Algorithm

Language: Python - Size: 861 KB - Last synced at: 4 months ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 0

qtle3/logistic-regression

A Python implementation of Logistic Regression to classify social network ads based on age and estimated salary, featuring data visualization and performance metrics such as confusion matrix and accuracy score.

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pabloelt/lead-scoring-analysis-and-segmentation

Lead Scoring Analysis and Segmentation. A lead scoring analysis is conducted for an online teaching company with a low client conversion rate. The goals are to reverse this trend by using a machine learning model based on available company data and to categorize customers with an effective segmentation.

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pabloelt/risk-scoring-for-a-neobank-company

A risk-scoring model is developed for a bank company using machine learning algorithms to assess the profitability of new loan applicants. The model predicts Expected Loss by analyzing Probability of Default, Exposure at Default, and Loss Given Default.

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dileepkorade/Machine-Learning_Projects

Projects based on Machine Leaning

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sultanazhari/prediction-model-of-customers-leaving

Bank Beta Company focus on retain existing customers, our task is to create a model that predicts whether or not a customer will leave the bank soon.

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IvanHanonoCozzetti/URL-Malware-Analyzer

Security tool that scans URLs and predicts if they are malicious or not, based on a Logistic Regression algorithm.

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Saket-Kr/ML-Prep

A repo holding the implementation as well as some theoretical explanation of the important relevant concepts. It is going to be in development for a long long time. I'll keep adding things everytime I have something to add to it, and I have the time for it. One can use it to learn the basics of Machine Learning from kind of scratch.

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Ruban2205/Iris_Classification

This repository contains the Iris Classification Machine Learning Project. Which is a comprehensive exploration of machine learning techniques applied to the classification of iris flowers into different species based on their physical characteristics.

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abhilas0/Predicting_Credit_Card_Approvals

Predicting Credit Card Approvals

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mnassrib/pca

This tutorial illustrates the advantages of using PCA for classification.

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div5yesh/machine-learning

Implementation of machine learning algorithms and evaluations on MNIST dataset.

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Nessrin1990/CodeClause_Churn-Prediction-in-Telecom-Industry-using-Logistic-Regression

Churn-Prediction-in-Telecom-Industry-using-Logistic-Regression

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ac005sheekar/Breast-Cancer-Detection-with-Pixel-Intensity

This is a Breast Cancer Detection project with unsupervised learning algorithmic approaches alongside Naive Bayes Classifier Algorithm, Logistic Regression and GaussianNB.

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Sonaxy/Heart_Failure_Prediction 📦

Heart Failure Prediction by developing various Supervised Learning algorithms in Python

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NimishNagapure/Problems_on_Logistic_Regression

➕ Solving Problems Using ➗ (✔ Logistic Regression Algorithm ✔)

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thenomaniqbal/LogisticRegression-BreastCancerDS

logistic regression from scratch using python to solve binary classification problem using breast cancer dataset from scikit-learn. A complete breakdown of logistic regression algorithm.

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Aakash1822/Fruit_prediction

Fruit Count prediction using its shape and size using Machine Learning

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Sarthak-Mohapatra/Building-Algorithm-from-scratch-for-prediction-of-Average-GPU-run-time-and-classifying-the-run-type.

As part of this project, I have developed algorithms from scratch using Gradient Descent method. The first algorithm developed will be used to predict the average GPU Run Time and the second algorithm will be used to classify a GPU run process as high or low time consuming process.

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Sarthak-Mohapatra/Classification-of-tumors-in-Human-Breast-as-Bening-or-Malignant-using-ML-Algorithms.

As part of this project, I have used Machine Learning (classification) algorithms for classification of tumors in Human Breasts as Non-Cancerous/ Benign or Cancerous/ Malignant tumors.

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SanketKaware/Cricket-Winner-Prediction-using-Python-Pandas-Scikit-learn-NumPy-libraries

Predicted the outcome of 2018 IPL matches using the Random Forest machine learning algorithm with an accuracy of 71%, which was greater than the accuracy of Logistic regression and SVM algorithm.

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shivamkc01/Predict_customer_churn

A step-by-step approach to predict customer attrition using supervised machine learning algorithms in Python. This is best for Beginner who wants to start with easy machine learning projects.

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Saadia-Hassan/ML-Classifiers

A simple classification problem where SVM, Logistic Regression, KNN and Decision Trees algorithms are used and the F1-score with Jaccard similarity scores are found out.

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vaitybharati/P28.-Supervised-ML---Logistic-Regression---Appointing-Attorney-or-not

Supervised-ML---Logistic-Regression---Appointing-Attorney-or-not. EDA, Model Building, Model Predictions, Testing Model Accuracy, ROC Curve plotting and finding AUC value.

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vaitybharati/Logistic-Regression

Logistic-Regression

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vaitybharati/Assignment-06-Logistic-Regression

Assignment-06-Logistic-Regression. Output variable -> y y -> Whether the client has subscribed a term deposit or not Binomial ("yes" or "no") Attribute information For bank dataset Input variables: # bank client data: 1 - age (numeric) 2 - job : type of job (categorical: "admin.","unknown","unemployed","management","housemaid","entrepreneur","student", "blue-collar","self-employed","retired","technician","services") 3 - marital : marital status (categorical: "married","divorced","single"; note: "divorced" means divorced or widowed) 4 - education (categorical: "unknown","secondary","primary","tertiary") 5 - default: has credit in default? (binary: "yes","no") 6 - balance: average yearly balance, in euros (numeric) 7 - housing: has housing loan? (binary: "yes","no") 8 - loan: has personal loan? (binary: "yes","no") # related with the last contact of the current campaign: 9 - contact: contact communication type (categorical: "unknown","telephone","cellular") 10 - day: last contact day of the month (numeric) 11 - month: last contact month of year (categorical: "jan", "feb", "mar", ..., "nov", "dec") 12 - duration: last contact duration, in seconds (numeric) # other attributes: 13 - campaign: number of contacts performed during this campaign and for this client (numeric, includes last contact) 14 - pdays: number of days that passed by after the client was last contacted from a previous campaign (numeric, -1 means client was not previously contacted) 15 - previous: number of contacts performed before this campaign and for this client (numeric) 16 - poutcome: outcome of the previous marketing campaign (categorical: "unknown","other","failure","success") Output variable (desired target): 17 - y - has the client subscribed a term deposit? (binary: "yes","no") 8. Missing Attribute Values: None

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prathmachowksey/Logistic-Regression

Logistic regression implementation in python.

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askreddii1234/AI-Projects

Logistic Regression algorithm to predict whether Ad clicks or not using customers data

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Sahil-Chavan/MicrosoftMalwareDetection

==>>Problem Statement : In the past few years, the malware industry has grown very rapidly that, the syndicates invest heavily in technologies to evade traditional protection, forcing the anti-malware groups/communities to build more robust softwares to detect and terminate these attacks. The major part of protecting a computer system from a malware attack is to identify whether a given piece of file/software is a malware. ==>>Source/Useful Link : Microsoft has been very active in building anti-malware products over the years and it runs it’s anti-malware utilities over <b>150 million computers</b> around the world. This generates tens of millions of daily data points to be analyzed as potential malware. In order to be effective in analyzing and classifying such large amounts of data, we need to be able to group them into groups and identify their respective families. -> Source: https://www.kaggle.com/c/malware-classification

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tahira2k16/Logistic-Regression-Projects

Logistic Regression Project

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KoolCards/StudentAlcohol

Logistic regression algorithm that predicts elevated alcohol levels in students

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suubh/Machine-Learning

It includes my work on Machine learning during Coursera Assignment. It includes Linear regression and Logistic regression working model .It also include Neural Network implementation and Backpropagation Algorithm .It also include SVM implementation and also a Spam Classifier using SVM.

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SaadTariq01DataAnalyst/Prediction-of-Bank-Churn-Customer

The goal of this project is to develop a machine learning model that can help banks to identify customers who are likely to churn and take appropriate measures to retain them

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felipexw/guessb

Webapp para classificar comentários (positivos, negativos e neutros) advindos do Facebook usando Natural Language Toolkit (NLTK) + Django e Bootstrap na interface Web.

Language: Python - Size: 10.3 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 0

jamestiotio/ml

SUTD 2021 50.007 Machine Learning Code Dump

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BigWheel92/Logistic-Regression

a vectorized binary logistic regression implementation in python.

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NehaPant14/Loan-Prediction

Loan Prediction using Classification Techniques

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akhileshravi/MultiLayerPerceptron

This is a repository for Multi-Layer Perceptron and Logistic Regression. There is a code (function) for Logistic Regression. SOme analysis is performed on the function. This is compared with the sklearn Logistic Regression function. Then, the decision boundary has also been plotted for the classification. The next part is the basic neural network. A class and a function has been created for this and it has been used for digit classification (mnist dataset).

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Ankit152/IMDB-sentiment-analysis

Sentiment analysis of IMDB dataset.

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shreyas-singhal/Lead-Scoring-Case-Study

X Education Organization wants to identify if a customer registered on their website for enquiry is a potential customer or not. Using past data to build a machine learning algorithm

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meuwebsite/Facebook--PredictCustumer-Click

Running a targetted marketing ads on facebook. The company wants to anaylze customer behaviour by predicting which customer clicks on the advertisement

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Jspano95/Retail-Customer-Classification-Modelling

Classification ML models for predicting customer outcomes (namely, whether they're likely to opt into email / catalog marketing) depending on customer demographics (age, proximity to store, gender, customer loyalty duration) as well as sales and shopping frequencies by department

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Coldwave96/MaliciousURLs

人工智能检测恶意URL

Language: Python - Size: 17 MB - Last synced at: over 2 years ago - Pushed at: almost 5 years ago - Stars: 10 - Forks: 9

ranjeetds/UCI-Spambase-spam-or-not-spam-detection

A simple Logistic regression classification to identify whether an email is spam or not spam built using python and scikit learn

Language: Python - Size: 160 KB - Last synced at: over 2 years ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 0

PaulaSanches/TrainingModels

Laboratory with random forest, logistic regression and SVM. The dataset used for this test is a set of points generated randomly with the following specification: • Number of Samples: 1200 • Number of Classes: 3 • Number of Features: 2 (Length and Width).

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vipulvs91/LitModel

Fire Incident risk classification Data Mining project

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saichandrareddy1/Machine_Learning_basics

This is repository about the MachineLaering Basics including all the Machine learning Algorithms

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SooyeonWon/predicting_default_risk

Supervised Learning and Classification Models

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sauriii98/Deep-Learning-algorithms

Implementation of all basic algorithms needed in Deep Learning

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PatilSukanya/Assignment-06.-Logistic-Regression

Used libraries and functions as follows:

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frapac/LogisticOptTools.jl

A package to fit logistic regression in pure Julia

Language: Julia - Size: 176 KB - Last synced at: about 2 months ago - Pushed at: about 5 years ago - Stars: 1 - Forks: 0

as3eem/AmazonFoodReview

Data Mining on Amazon Fine Food Reviews Dataset. It also depicts a detailed comparative analysis of accuracies in various ML-Models.

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easonlai/diabetes_prediction_lr_xgb

This is a sample code repository to leverage classic "Pima Indians Diabetes" from UCI to perform diabetes classification by Logistic Regression & Gradient Boosting algorithms.

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prabhatk579/logistic-regression-from-scratch

Applying logistic regression using an user defined function on iris dataset

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harshithshankar13/Machine-Deep_Learning

Contains implemented Machine learning and deep learning code and description.

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ligerfotis/CSE6363_Machine_Learning

Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21

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sanikamal/fake-news-detector

Fake News Detection with Machine Learning

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Rioba-Ian/Deep_Learning

Deep learning projects using Pytorch and tensorflow.

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khadkarajesh/wine-prediction

White and Red Wine classification using logistic regression

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Pushpendra9350/Sentiment-prediction-on-reviews

This is a single webpage application in which we need to enter a review and this will tell you whether the review is positive or not. To make this work NLP techniques and Logistic regression algorithm is used with 94% accuracy

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shreeratn/Predicting-Credit-Card-Approval

Build a machine learning model to predict if a credit card application will get approved.

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tofti/python-logisticregression

python-logisticregression

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piygot5/machine-learning

code related to ML

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sichkar-valentyn/Logistic_Regression

Implementing Logistic Regression for the Image Recognition task

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KevinB-a/turn_over_at_work

machine learning (logistic regression and other algorithm )

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micb21/Logistic-Regression_Python

Logistic Regression_Python

Language: Python - Size: 29.3 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

shilpakancharla/hate-speech

As citizens, how can we keep track of hate speech online that's affecting our fellow peers and neighbors? While I believe there are myriad solutions to helping each other out, I wanted to try a solution using machine learning models. Machine learning classifiers, alongside a vast amount of data gathered through API calls, can offer valid solutions to organizations and companies attempting to monitoring content on their platforms. Ultimately, a logistic regression classifier was created that achieved 98% accuracy when classifying tweets as positive (non-offensive) and negative (offensive).

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chicks2014/Predict_affairs

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boosuro/predicting_numbers_in_image_with_logistic_regression

predicting numbers in image with logistic regression

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safesit23/ML-Workshop

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Rodolfo9706/Simple-perceptron

In the following work a simple structured perceptron is shown, the libraries used are numpy for the matrix operations, maplotlib to obtain the graphs. The input must approach the chosen target, which is a logic gate. I hope it is useful

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RyanLBuchanan/Logistic_Regression

Logistic Regression tutorial from Machine Learning A-Z - SuperDataScience - Input by Ryan L Buchanan 25SEP20

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Abhijit2505/Cat-Photo-Classification

This repository contains two models having Two - layers ANN and L - layers ANN respectively to classify Cat photo and Non-Cat photo. This ANN works on the mathematical principles of Logistic Regression and Cross Entropy.

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Abhijit2505/Data-Science

This repository containts the projects that I have done along With my Data Science MOOCs from Coursera.

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aryanjain28/Blog---Logistic-Regression

This blog is my attempt to explain logistic regression in the easiest way possible.

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Lokeshrathi/Diabetes-Prediction

Diabetes Prediction using Classification Algorithm

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sakusuma/TelecomChurn

The project is based on Indian and Southeast Asian market where mostly prepaid payment model is prevelant In this project we will use the usage-based chrun definition i.e. customers who have not done any usage either incoming or outgoing in terms of calls, internet etc. over a period of time. We focus only the High Value customers, as typically 80% of the revenue comes from top 20% of the customers The dataset spans data of four consecutive months between June - September. The objective is to predict the churn in the last month using the data from the first three months. There are typically three phases of a customer lifecycle - (a) Good Phase where the customer is happy with services. We have assumed month 6 and 7 as Good Phase period here.(b) Action Phase where customer experience starts to sore. We have assumed the 3rd month i.e. month 8 here for this (c) Churn Phase where the customer is said to have churned. This is equivalent to the month 9 here.

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