Heart disease prediction with logistic regression using SAS Studio. The dataset is taken from UCI Machine Learning about heart disease.
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Updated
Apr 20, 2023 - SAS
Heart disease prediction with logistic regression using SAS Studio. The dataset is taken from UCI Machine Learning about heart disease.
A credit scoring model to predict credit worthiness of an individual based on demographics, loan size and credit history using logistic regression.
Loan eligibility prediction in Lasiandra Finance Inc. (LFI) using SAS studio.
Classified the restaurants into two tiers based on their user ratings. Used Random Forest to predict the Important Attributes which contribute to the success rate of a Restaurant. Used logistic regression to predict which tier has better success rate based on certain attributes using SAS.
Performed statistical analysis and modelling using Linear Regression, Logistic Regression and ANOVA on short-term property rentals data set with SAS
logistic model to predict whether an individual’s annual income is above 50000
This code uses SAS for exploration of data and to identify possibility of back orders in supply chain using Logistic Regression
Testing carpet samples for chemical compounds to determine their age using SAS. Dataset can be found in the README file.
KeepCoding Bootcamp Big Data & Machine Learning - Práctica Advanced Data Mining
Worked on building a predictive model by considering multi collinearity and applying regression technique as well as other machine learning concepts related to factors or variables using SAS programming.
Study based on segmentation, linear regression and logistics regression using SAS and R.
Project Data Science Salary Prediction using SAS.
Performed Logistic Regression on two different (Movie's Rating and Insurance claim) dataset. Explored statistical significance of various variables with respect to the target variable.
A Predictive Analysis of H1B Dataset using both supervised and unsupervised learning
SAS code for prediction of development of Coronary Heart Disease
Developing an unbiased probability model that deems profitable to a mobile app creator in terms of identifying right customers who would install the app while minimizing advertising costs
Marketing in a Digital World - Implications of Internet Core Trends for TV Advertising
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