Publications by Salma Elshahawy, Mael Illien, Dhairav Chhatbar
DATA612: Recommender Systems - Final Project
library(recommenderlab) library(recommenderlabBX) library(ggplot2) library(dplyr) library(tidyr) library(data.table) library(kableExtra) data("BX") General Goals For the final project for this course I would like to use the material learned in the course to build a recommendation model on the Book-Crossing Dataset. In determining the most...
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DATA612: Recommender Systems - Research Discussion 4
It is certainly true that recommender systems can have a tendency to funnel a user into a feedback bubble which can have an overall detrimental effect the sharpest example of this is in the New York Times article. It does not help that we encounter such recommendations everywhere on any technology platform. However, tube sites and social media pl...
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DATA612: Recommender Systems - Research Discussion 3
As more systems and sectors are driven by predictive analytics, there is increasing awareness of the possibility and pitfalls of algorithmic discrimination. In what ways do you think Recommender Systems reinforce human bias? Reflecting on the techniques we have covered, do you think recommender systems reinforce or help to prevent unethical targe...
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DATA621 - Assignment 1
Data 621 Homework1 Introduction A wealth of statistics are collected in sports, and baseball is no exception. The exploration and modeling that follows is based on a “Moneyball” dataset where the response variable is the number of wins for a given team for a particular season. The aim of this report is to build models and identify the one th...
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DATA621 - Assignment 2
Data 621 Homework2 1. Fetching Data data_raw <- read.csv("https://raw.githubusercontent.com/salma71/Data_621/master/HW_2/classification-output-data.csv") data <- data_raw %>% select(class, scored.class, scored.probability) data 2. Raw confusion matrix # Columns represent the actual class # Rows represent the score/predicted class t <- with(...
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DATA621 - Blog 5
Panel data are a type of longitudinal data, or data collected at different points in time. Panel data models provide information on individual behavior, both across individuals and over time. The data and models have both cross-sectional and time-series dimensions. In this we will attempt panel models on a stocks dataset as this dataset provides ...
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DATA621 - Blog 3
Poisson Regression Poisson Regression model is used to model count data. These are response variables that are discrete data with non-negative, whole (non-fraction) integer values that count something. In other words, it shows which explanatory variables have a notable effect on the response variable. Poisson Regression involves regression models...
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DATA621 - Blog 1
Linear Regression Linear regression is the process of determining the relationship between two or more variables, specifically it is a relationship between a dependent variable that is continuous and one or more independent variables that are either categorial or numerical. The independent variable(s) is known as the predictor variables and depen...
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DATA608 - Module 5
DATA608 - Module 5: Javascript Dhairav Chhatbar Question 1: Create a function to reverse any word that you type in. This can be typed into either an input box or an alert box, and then print the result in a box or on the webpage Reverse Question 2: Create a function that takes an input number, and prints a table with the first 20 multiples of ...
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DATA621 - Assignment 3
Data 621 Homework3 Introduction For this assignment, we were tasked with building a binary logistic regression model from a dataset containing information on crime in various neighborhoods of a major city. Given a vector of predictors, we seek to predict whether the neighborhood crime rate is above the median. data_train <- read.csv("https://raw...
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