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Visualisation
Some codes to facilitate different types of visualisationLogistic-Regression-Bank-Model
We run a logistic regression to determine significant variables affecting the probability of sale of bank's productsHands-on-Excercises
These exercises were given to us as the ending slides of the first PPT shared with us. These exercises all are meant to give us hands on experience of using RLogistic-Regression-Survival-State
In this scenario, we were given data of the titanic's passengers and we had to predict survival rates. Utilised K fold valisation as well post splitting the data into train and test setSupport-Vector-Machine
A suggestive code for the utilization of support vector machine for Data scienceControl-Statement-inputs
A list of operators and control statements for quick reference, to facilitate R operationsSome-basics-of-Data-Manipulation
This repository will take you through some basic know how regarding data manipulationData-Frame-Methods
This repository deals with Methods to work on Data Frames for reference purposesAssessing-Logistic-Regression
This Repository provides Tools to assess Methods of Logistic Regression like Gains Chart, Confusion Matrix etc.R-Functions-intro-and-illustration
This repository deals with different types of functions such as numeric, statistical, character etc.CART-Decision-Tree-Algorithms-
CART i.e Classification and Regression Trees introduced by Leo Breiman. The complexity of the decision tree is defined as the number of splits in the tree.CHAID-decision-tree-techniques-
CHAID stands for "Chi Square Automatic interaction detector" devised by Kass in 1980 in South Africa. CHAID creates all possible cross tabulations for each categorical predictor until the best outcome is achieved and no further splitting can be performed.In-code-assignments
These were some assignments given to us between the codes provided for learning purposes. They have correspondence with the hands on excercisesRandom-Forest
On a Titanic data set, on which we had earlier run the logistic regression survival scenario we now apply Random Forest (an ensemble learning method for classification) for purposes of illustrationLove Open Source and this site? Check out how you can help us