xG MATLAB Model

To run: 

make sure you have soccer_workspace.mat,  (**ANY OTHER WORKSPACES**)

import Oxy shot data as a table 

run main file: Project_main.m

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This zip file should contain:

soccer_workspace.mat, (**ANY OTHER WORKSPACES**)

removeNAN- this function removes data entries with NAN values in the
relevant feature columns

splitData- splits data and labels into training, development,and test sets
    also randomizes order

EstablishPerceptron- this is my perceptron function from project one.
takes in data and labels, trains a perceptron assuming linear
separability

AdjustWeight- called in EstablishPerceptron, adjusts weights 
and b simultaneously

Perceive- tests perceptron (or SVM). uses decision boundary from EstablishPerceptron to predict y
values for an unknown dataset

establishSVM- turns decision boundary from EstablishPerceptron into support 
vector machine. uses gradient descent to loop through data, updating weights and b

CrossVal- cross validates SVM across 8 folds

OptimizeSVM- calls all the former functions to train an optimal SVM and test it

bootstrap- gives 20 sets of test results for two input models across 1 bootstrapped test set

ttestForestSVM- gives statistical analysis of bootstapped test outputs

ForstVsSVM- the SVM poo-bah script, which compares the results of the optimized SVM to the pre-trained optimized random forest using the above methods

preProcess- a script w collection of methods which was used to process data

SVMtester- a script previously used to compare results from SVM's tested on datasets with different degrees of balance

gamePerf – a function that performs xG analysis on each recorded game (16 total) by splitting up the input shot data based on each events game ID. It outputs information about the each game’s expected and actual outcome.

goalPerf – a function that performs broad xG analysis for all input shot data, outputting information about total goals scored against expectation throughout the season, as well as the average number of goals scored per game against expectation.

Organize – Sorts and organizes input data for use in xG analysis later on.