Publications by Jay Lee
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Abstract Using the R library to calculate the VaR for my investment portfolio which is Kinetics Paradigm Fund No Load Class (WWNPX). Value at risk (VaR) is a statistic that quantifies the extent of possible financial losses during Sep 2023. Scenario: Case 1 You are a new graduate from a major university and have gotten a job at a major investment f...
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Abstract Using the R library to calculate the VaR for my investment portfolio which is Kinetics Paradigm Fund No Load Class (WWNPX). Value at risk (VaR) is a statistic that quantifies the extent of possible financial losses during Sep 2023. Scenario: Case 1 You are a new graduate from a major university and have gotten a job at a major investment f...
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Data cleaning We see there is NA under quite a lot of columns by looking at the summary, however, it is hard to tell for “Brand Code” since it is only showing the class is character due to the column format. Then we sum the na to check it, and it has 120 NA. Therefore, we try to label it as NA instead of letting it blank the data before working...
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Recently, I saw a news that police increased patrols outside schools in Manhattan on Wednesday after a series of possibly connected shootings left three people injured. It is always shocking to see school may not be the safest place when it should be. Also it remind me there is a mass subway shooting in Brooklyn back to Spring 2022 which is a year ...
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rules <- apriori(GroceryDS, parameter = list(supp = 0.001, conf = 0.5, maxlen=3)) ## Apriori ## ## Parameter specification: ## confidence minval smax arem aval originalSupport maxtime support minlen ## 0.5 0.1 1 none FALSE TRUE 5 0.001 1 ## maxlen target ext ## 3 rules TRUE ## ## Algorithmic contro...
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<!doctype html> <img src="https://github.com/charleyferrari/CUNY_DATA_608/blob/master/module6/d3_lab/streamgraph.jpg?raw=true" height="600px" width="1200px" /> <h3>Assignment 6: D3 lab</h3> <p>D3.js is a powerful data visualization library. Rather than being based around existing plot types, d3 allows you to bind any html element. This power is...
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library(mlbench) set.seed(200) simulated <- mlbench.friedman1(200, sd = 1) simulated <- cbind(simulated$x, simulated$y) simulated <- as.data.frame(simulated) colnames(simulated)[ncol(simulated)] <- "y" 8.1 a Fit a random forest model to all of the predictors, then estimate the variable importance scores: Did the random forest model significantly us...
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7.2. Friedman (1991) introduced several benchmark data sets create by simulation. One of these simulations used the following nonlinear equation to create data: y = 10 sin(πx1x2) + 20(x3 − 0.5)2 + 10x4 + 5x5 + N(0, σ2) where the x values are random variables uniformly distributed between [0, 1] (there are also 5 other non-informative variables ...
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library(caret) ## Loading required package: ggplot2 ## Loading required package: lattice library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(pls) ## ## Attachi...
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