Publications by Alexander Ng
Data 624 HW9 Tree/Rule Based Models
Data 624 HW 9 (Week 12) Regression Trees and Rule-Based Models Alexander Ng Due 11/21/2021 Overview Exercises from Kuhn and Johnson Applied Predictive Modeling, Chapter 8 Regression Trees and Rule-Based Models. All R code is displayed at the end for clarity. Exercise 8.1 Recreate the simulated data from Exercise 7.2. set.seed(200) simulated = ml...
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Data 624 Project 1 Fall 2021
Data 624 PROJECT 1 (Week 9) Forecasting ATM, Residential Power and Waterpipe Flow Alexander Ng Due 10/31/2021 # Conditional Code Evaluation is managed here. runPartA = TRUE runPartB = TRUE runPartC = TRUE runOncePartC = FALSE # Used to load and convert XLSX files that cause unsurpressable warnings. cross_validation_stepsize = 1 # Make this equ...
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Data 624 HW5 Exponential Smoothing Methods
Data 624 HW 5 (Week 6) Exponential Time Series Data Processing/Overfitting Alexander Ng Due 10/10/2021 Overview Exercises from Hyndman & Athanosopoulos, Forecasting: Principles and Practice, Chapter 8 Exponential Smoothing. All R code is displayed at the end for clarity. Exercise 8.1 Consider the the number of pigs slaughtered in Victoria, avail...
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Data 624 HW4 Data Preprocessing
Data 624 HW 4 (Week 5) Data Preprocessing Data Processing/Overfitting Alexander Ng Due 10/3/2021 Overview Exercises from Kuhn & Johnson, Applied Predictive Modeling, Chapter 3 Data Preprocessing. All R code is displayed at the end for clarity. Exercise 3.1 Statement The UC Irvine Machine Learning Repository contains a data set related to glass i...
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Citations and References for Data Scientists in RStudio and Zotero
This article demonstrates how RStudio, Zotero and related tools can produce scholarly citations in a data science workflow. Data scientists typically code and write text in software tools like RStudio or Jupyter where citations, references and bibliographies are distant afterthoughts. Word processors like Microsoft Word or Google Docs support sch...
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Data 624 HW3 Time Series
Data 624 HW 3 (Week 4) Time Series Alexander Ng Due 09/26/2021 Overview Exercises from Hyndman and Athanosopoulos, Forecasting: Principles and Practice, 3rd Edition, Chapter 5 The forecaster’s toolbox. library(fpp3) library(kableExtra) library(cowplot) Exercise 5.1 Produce forecasts for the following series using whichever of NAIVE(y), SNAIVE(...
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Predictive Analytics DATA 624 HW2
Data 624 HW 2 (Week 3) Time Series Alexander Ng Due 09/19/2021 Overview Exercises from Hyndman and Athanosopoulos, Forecasting: Principles and Practice, 3rd Edition, Chapter 3 Time series decomposition. library(fpp3) library(kableExtra) Exercise 3.1 Consider the GDP information in global_economy. Plot the GDP per capita for each country over tim...
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Data 624 HW1
Data 624 HW 1 (Week 2) Time Series Alexander Ng 09/12/2021 Overview Exercises from Hyndman and Athanosopoulos, Forecasting: Principles and Practice, 3rd Edition, Chapter 2 Time series graphics. library(fpp3) Exercise 2.1 Use the help function to explore what the series gafa_stock, PBS, vic_elec and pelt represent. Use autoplot() to plot some of...
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Data 624 HW6 ARIMA
Data 624 HW 6 (Week 8) ARIMA Alexander Ng Due 10/24/2021 Overview Exercises from Hyndman & Athanosopoulos, Forecasting: Principles and Practice, Chapter 9 ARIMA models. All R code is displayed at the end for clarity. Exercise 9.1 Figure 9.32 shows the ACFs for 36 random numbers, 360 random numbers and 1,000 random numbers. Explain the differenc...
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Data 624 HW7 Linear Regression
Data 624 HW 7 (Week 10) Linear Regression Alexander Ng Due 11/7/2021 Overview Exercises from Kuhn and Johnson Applied Predictive Modeling, Chapter 6 Linear Regression and Its Cousins. All R code is displayed at the end for clarity. Exercise 6.2 Developing a model to predict permeability (see Sect. 1.4) could save significant resources for a phar...
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