Using decision tree, logistic regression, neural network of data mining techniques to analysis and compare them choose the best one and Describe the advantages and disadvantages

Requirment

Using decision tree, logistic regression, neural network of data mining techniques to analysis and compare them choose the best one and Describe the advantages and disadvantages

Analyze three models

Forecast the direction of Boston housing prices

And find out which elements are most relevant to house prices and describe their relevance

Report

•executive summary of project 

•business problem/opportunity (from proposal) 

•specific business objective(s) (from proposal) 

•process followed for selecting and gathering data

•discussion of preliminary data exploration and findings 

•description of data preparation – repairs, replacements, reductions, partitions, derivations, transformations and variable clustering 

•description of data modeling/analyses and assessments

•explanation of model comparisons and model selection

•conclusions and recommendations (i.e., what did you learn from the analysis; did you meet your stated business objective(s); how can the results of your analysis address the business problem/opportunity; what further analyses, that builds on your work, can be in done in the future)

Concerns housing values in suburbs of Boston.

  1. Number of Instances: 506
  2. Number of Attributes: 13 continuous attributes (including “class”
    attribute “MEDV”), 1 binary-valued attribute.
  3. Attribute Information:
    1. CRIM per capita crime rate by town
  1. ZN proportion of residential land zoned for lots over
    25,000 sq.ft.
  2. INDUS proportion of non-retail business acres per town
  3. CHAS Charles River dummy variable (= 1 if tract bounds
    river; 0 otherwise)
  4. NOX nitric oxides concentration (parts per 10 million)
  5. RM average number of rooms per dwelling
  6. AGE proportion of owner-occupied units built prior to 1940
  7. DIS weighted distances to five Boston employment centres
  8. RAD index of accessibility to radial highways
  9. TAX full-value property-tax rate per $10,000
  10. PTRATIO pupil-teacher ratio by town
  11. B 1000(Bk – 0.63)^2 where Bk is the proportion of blacks
    by town
  12. LSTAT % lower status of the population
  13. MEDV Median value of owner-occupied homes in $1000’s
  14. Missing Attribute Values: None.
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