Publications by LeTicia Cancel
Data607_Presentation
Text Analysis in Customer ServiceLeTicia CancelOctober 28, 2020 Quantitative Analysis Quantitative analysis is an easy way measure performance in a company. Response Time Resolution Time Customer Rating/Score Zapier customer support average response time. Qualitative Analysis How do customers really feel about a company or product? Custome...
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HWK9_Data607_F20
Libraries #install.packages("prettydoc") library(jsonlite) library(dplyr) library(ggplot2) Get Data The API used for this assignment is for the most popular articles. #most viewed articles in the past 30 days most_popular <- fromJSON("https://api.nytimes.com/svc/mostpopular/v2/viewed/30.json?api-key=PznXIQ8GgeAC84XdXYy34uS8IGQhqqyA") #crea...
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Homework11_Data607_F20
Recommender System The recommender system I will analyze is Puritan’s Pride. It is an online store that sells herbs and supplements. Scenario Design Analysis: Who are the target users? The target users are individuals who take supplements and want to purchase them in bulk for a bargain price. What are their key goals? Their goal is to prov...
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Homework10_Data607_F20
Original Code The code in sections 2.1 - 2.3 were copied from Text Mining with R: Chapter 21 #libraries #install.packages("textdata") library(tidytext) library(janeaustenr) library(dplyr) library(stringr) library(tidyr) library(ggplot2) library(tidyverse) Section 2.1 The sentiments dataset get_sentiments("afinn") get_sentiments("bing") ...
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Project4_Data607
Document Classification Acquiring the Data Creating Document Term Matrix Random Forest Model & Prediction Confusion Matrix Random Forest SVM Model and Prediction SVM Model Confusion Matrix Conclusion Document Classification It can be useful to be able to classify new “test” documents using already classified “training” documents. A commo...
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Final Project Data 607 F20
Fake News! Data Tidying Training a model Analysis Exploratory Usage Of Our Models Exploring Data with Visualizations Conclusion Sources Fake News! Our project started with the seemingly innocuous proposal of creating an algorithm to identify real vs fake news, a classification that has had a lot of cache over the last half decade. Is it possibl...
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Visuals_For_Final_Data607
Introduction Visualizations in this file were created to support the Final Project where we analyze news articles classified as “Real” news vs. “Fake” news. r2d3 Top Words Create dataframe of true and fake words to use with r2d3 #load true and fake data into dataframes true_df <-read.csv(here('data','csv','true_df.csv'), encoding="asci...
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LCancel_DATA605_Final
#libraries library(tidyr) library(dplyr) library(pander) library(ggplot2) library(corrplot) library(matlib) library(matrixcalc) library(MASS) library(mltools) library(caTools) Problem 1 Using R, generate a random variable X that has 10,000 random uniform numbers from 1 to N, where N can be any number of your choosing greater than or equal to 6. ...
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DATA 621 Homework 3
DATA EXPLORATION Data Summary summary(train_df) ## zn indus chas nox ## Min. : 0.00 Min. : 0.460 Min. :0.00000 Min. :0.3890 ## 1st Qu.: 0.00 1st Qu.: 5.145 1st Qu.:0.00000 1st Qu.:0.4480 ## Median : 0.00 Median : 9.690 Median :0.00000 Median :0.5380 ## ...
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DATA608 HWK 1
#libraries library(dplyr) library(ggplot2) Principles of Data Visualization and Introduction to ggplot2 I have provided you with data about the 5,000 fastest growing companies in the US, as compiled by Inc. magazine. lets read this in: inc <- read.csv("https://raw.githubusercontent.com/charleyferrari/CUNY_DATA_608/master/module1/Data/inc5000_d...
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