Simple Genetic Algorithm
A simple Genetic Algorithm library
To begin, run the install.R file to install the GA library and set the R package location (NOTE YOU
DONT DO THE SECOND PART IF YOU ARE USING YOUR OWN COMPUTER).
The example we are going to build
Lab Week 6: Using Artificial Neural
Networks, Scaling and Responses
There are two goals for this lab: 1. to show you how to setup and predict using an Artificial
Neural Network (ANN); and 2. to show how to do predictions given a model. We will use
Chapter 2
Linear Regression I
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The normal linear regression takes the form
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yi = ﬁe + 512311-1— 529% + ' ' ‘ + ﬁpifpi ﬁg; (2.1)
o y,- is the ith observed value of the response variable, i = 1, - - - ,n
0 mm- is the ith observed value
INFO 324: Lab 4, Decision Trees
The goal of this lab is to show you one way that a decision tree can be created in R, using
the command rpart. We will apply this to the Olive dataset you might want to go back and
look at the SOM examples using this data t
Lab 3: R and Clustering
The goal of this lab is to extend your understanding of R (Task 1), create a dendrogram (Task 2) and
examine some SOMS (Task 3). The concepts of a dendrogram and SOM have been briefly introduced
in lecture 4.
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Download and
INFO 324-424: Lab 2, More R and PCA
The goal of this lab is to extend your understanding of R and to examine how principal component
analysis (PCA) can be used to understand relationships in a multivariate dataset.
BEFORE COMMENCING: install the package "
INFO 324/424: Lab 1, Getting Started
The goal of this lab is to introduce you to the R toolbox. By the end of this lab, you should be
comfortable with entering commands into the R environment, editing and running scripts within R,
and understand some basi
INTRODUCTION TO R: DATA STRUCTURES AND OPERATIONS
1. PRECURSOR
This lab introduces some of the basic concepts of data structures in R. This is
important because you will often be accessing and manipulating a dataset, either
as an aid to visualizing the da