Publications by Husna Aydadenta
Bank Marketing Classification
Introduction Background The data is retrieved from UCI machine learning repository (https://archive-beta.ics.uci.edu/ml/datasets/bank+marketing) and is about a direct marketing campaign(phone calls) of a Portuguese bank. The customer service center of the bank calls customers to promote its term deposit product. They collect customers basic inform...
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Heart Disease Prediction using Logistic Regression and K-Nearest Neighbors
Heart Disease Prediction using Logistic Regression and K-Nearest Neighbors Heart Disease Prediction using Logistic Regression and K-Nearest Neighbors Introduction Objective Data Source Library Data Preparation Load Data Data Wrangling Explanatory Data Analysis Proportions Target Class Missing Value Correlation ...
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Exploratory Data Analysis Titanic
Introduction Data Source There is a complete database of all passengers on the titanic and it contains data as to who did and did not survive. This data is broken into two datasets. The training data contains who did and did not survive and the test dataset is missing that information. I am going to use the titanic dataset from https://www.kaggle....
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Crime Rate Prediction
Introduction This report describe Crime Prediction Linear Regression Analysis using Crime Dataset. The dataset used by criminologists to study the effect of punishment regimes on crime rates. Using linear regression analysis, we are going to build a model to predict crime rate based on various factors that influence it. Load Package These are ...
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House Price Prediction using Regression Algorithm
Description This report describe house price prediction using regression model. The dataset used in this project is the real estate data from Kaggle. https://www.kaggle.com/shree1992/housedata Report Outline: 1. Data Extraction 2. Exploratory Data Analysis 3. Data Preparation 4. Modelling 5. Evaluation 6. Recommendation 1. Data Extraction ...
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Banknote Authentication
Description This report describes Banknotes Authentication prediction using classification model. The dataset used in this project is the banknotes authentication data from UCI Machine Learning Repository. https://archive.ics.uci.edu/ml/datasets/banknote+authentication Data were extracted from images that were taken from genuine and forged bankno...
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