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Simultaneous prediction of symptom severity and cause in data from a test battery for Parkinson patients, using machine learning methods
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2009 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

The main purpose of this thesis project is to prediction of symptom severity and cause in data from test battery of the Parkinson’s disease patient, which is based on data mining. The collection of the data is from test battery on a hand in computer. We use the Chi-Square method and check which variables are important and which are not important. Then we apply different data mining techniques on our normalize data and check which technique or method gives good results. The implementation of this thesis is in WEKA. We normalize our data and then apply different methods on this data. The methods which we used are Naïve Bayes, CART and KNN. We draw the Bland Altman and Spearman’s Correlation for checking the final results and prediction of data. The Bland Altman tells how the percentage of our confident level in this data is correct and Spearman’s Correlation tells us our relationship is strong. On the basis of results and analysis we see all three methods give nearly same results. But if we see our CART (J48 Decision Tree) it gives good result of under predicted and over predicted values that’s lies between -2 to +2. The correlation between the Actual and Predicted values is 0,794in CART. Cause gives the better percentage classification result then disability because it can use two classes.

Place, publisher, year, edition, pages
Borlänge, 2009. , 37 p.
Keyword [en]
Naïve Bayes, CART, KNN
Identifiers
URN: urn:nbn:se:du-4586OAI: oai:dalea.du.se:4586DiVA: diva2:518805
Uppsok
Technology
Supervisors
Available from: 2010-03-12 Created: 2010-03-12 Last updated: 2012-04-24Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf