Publications by Jean Jimenez
Data 622 Homework 3
Assignment Instructions Perform an analysis of the dataset(s) used in Homework #2 using the SVM algorithm. Compare the results with the results from previous homework. Literature Review Three Articles on SVM vs Decision Tree on Diabetes: M. F. Faruque, Asaduzzaman and I. H. Sarker, “Performance Analysis of Machine Learning Techniques to Pred...
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Data 622 HW#2 CUNY SPS
Assignment Instructions Based on the latest topics presented, choose a dataset of your choice and create a Decision Tree where you can solve a classification problem and predict the outcome of a particular feature or detail of the data used. Switch variables* to generate 2 decision trees and compare the results. Create a random forest and analy...
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Determinants of Recurrent Stroke Incidence in a Clinical Sample
Determinants of Recurrent Stroke Incidence in a Clinical Sample Packages library(dplyr) ## Warning: package 'dplyr' was built under R version 4.3.2 ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, se...
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Visualizing Discrete and Continuous Distributions
Introduction When building a data based model, it is important to know what kind of distribution the data follows. There are different types of distributions: discrete and continuous. Each type has its own set of characteristics and implications for analysis, making the ability to visualize and interpret these distributions fundamental for anyo...
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Dealing with Missing Data Using LOCF
What is LOCF? Missing data is a common issue in many real-world datasets, leading to challenges in analysis and model training. One technique to handle missing data, particularly in time series or longitudinal data, is the Last Observation Carried Forward (LOCF) method. LOCF fills missing observations with the last available non-missing value. ...
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Evaluating Diagnostic Imaging with Sensitivity and Specificity
Introduction As a researcher that works in the field of radiology, Sensitivity and Specificity are two important values that are used to evaluate diagnostic imaging modalities. After all, it is important to know whether or not a specific type of scan (MRI, CT, Ultra Sound) is appropriate for detecting the condition in question. In this tutorial...
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Using F1 Score to Evaluate Logistic Regression Models
Using F1 Score to Evaluate Logistic Regression Models Introduction The F1 score is a measure of a model’s accuracy that considers both precision and recall to compute the score. Precision is the number of true positives divided by the number of all positive predictions, and recall is the number of true positives divided by the number of posit...
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Blog 1 Data 621
Simple Linear Regression of Stroke Dataset library(tidyverse) ## Warning: package 'dplyr' was built under R version 4.3.2 ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr ...
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Data 621 HW3
Logistic Regression of Crime Data Part 1: Training-Data Exploration library(dplyr) ## Warning: package 'dplyr' was built under R version 4.3.2 ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff...
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Data 608 Story 2
FED Inflation and Unemployment Introduction The Federal Reserve (or the Fed), plays an important role in the United States economy. Established by Congress, its dual mandate is controlling inflation and making sure unemployment is low. The Consumer Price Index (CPI) is a indicator of inflation. It reflects the changes in the cost of goods and s...
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