+1-415-670-9189
info@expertsmind.com
Compute color histograms and construct arff files
Course:- Software Engineering
Reference No.:- EM13882625




Assignment Help
Expertsmind Rated 4.9 / 5 based on 47215 reviews.
Review Site
Assignment Help >> Software Engineering

Project Exercises

Part I. Construct training data files (ARFF files) using the training image data for three different bin numbers (i.e., number_of_bins = 8, 64 and 512). The number of training data files should be three.

Part II. Construct the five different classifier models using each training data file. The five classification methods are as follows:

1) Naïve Bayes Classifier
2) C4.5 Classifier
3) k-Nearest-Neighbor Classifiers
4) Multilayer Neural Network
5) Support Vector Classifier

Part III. Construct test data files (ARFF files) using the test image data per each category for three different bin numbers. The total number of test data files should be 21 (=7*3) in this case.

Part IV. Compare the prediction accuracies among five different classifiers for each category

Part V. Construct test data files (ARFF files) using all test image data for three different bin numbers. The total number of test data files should be three in this case. (You can easily construct this three test data files by combining the test data files constructed in Part III)

Part VI. Compare the prediction accuracies among five different classifiers for overall test data

- You CAN compute color histograms and construct ARFF files

a) Manually by using MS-Excel and/or any text editor (wordpad, textpad, etc)

b) Automatically by developing your own program with any programming language such as C, C++, Java, etc.

Part VII. Project Submission.

1. A project report (PDF file observe CSC573 presentation standards) describing
1. A comprehensive description of each classifier.
2. Accuracy comparison for each category preformed in Part IV
3. Accuracy comparison for overall test image preformed in Part VI
4. Your conclusions based on your observations

Answered:-

Verified Expert


Preview Container content

Contents
Naïve Bayes Classifier 3
C4.5 Classifier 3
K-Nearest-Neighbor Classifiers 4
Multilayer Neural Network 4
Support Vector Classifier 5
Code 5
Comparison and Conclusion 11

Naïve Classifier works on the probabilistic distribution which can set a standard way on the text retrieval system. The categorization and documents judgment is based on handling the models which can match the problems. The instance of Bayes classification depends on the values and classify to hold the probability model efficiently based on parameterized estimation. The Bayesian probability directs to hold the probabilistic output which can outline important pattern of formulation and growth.

It is important for building up a decision tree which was earlier identified using the ID3 algorithm. There are statistical classification that directs to set up the information entropy system and represent the attributes of data depending upon effective splitting. The entropy enrichment is normalized with usage of the samples which are in same class. The creation of lead nodes are important for the information gain pattern. The encountering of different nodes direct to handle the expected value.




Put your comment
 
Minimize


Ask Question & Get Answers from Experts
Browse some more (Software Engineering) Materials
Write in pseudocode an algorithm that receives as input the root of a tree and it returns true if the tree is a proper binary tree (i.e. each internal node has 2 children) and
Modularity can have a negative as well as a positive effect. A program that is overmodularized performs its operations in very small modules, so a reader has trouble acqu
Suppose you are tasked with coming up with a system development approach for the following project: John's shoe store which operates a chain of local stores in Chicago wants
At this point, you want to put together the work that has been completed to deliver a working program for alpha testing. You will combine the elements you have written to th
What do you know about focused Linux distributions? If nothing, what can you find out by searching the Web? By "focused" we mean distributions that exist primarily for a spe
What is the effect of reading up and writing down restrictions imposed by the Bell-LaPadula model? And what is the effect of reading down and writing up restrictions imposed
Identify the Virus Software running on your computer. Is your Virus Software current and up-to-date. Have you downloaded the latest virus definitions? If not, do so and note
An analysis rule of thumb is, "The Model should focus on requirements that are visible within the problem or business domain". Can there be any other hidden requirements? If y