Lab Assignment 7 - Achu0015/BigDataAna-App-SP2K17 GitHub Wiki

                                             Lab Assignment
  1. Using Tensorflow implement Linear Regression for Boston dataset

Here I have used various packages like sklearn, pandas, numpy, matplotlib. Below are the reference websites I have used

https://www.youtube.com/watch?v=zNalsMIB3NE

https://shankarmsy.github.io/stories/linear-reg-sklearn.html

This dataset concerns housing values of suburb regions in Boston. The below is the information about 14 attributes

  1. CRIM: per capita crime rate by town
  2. ZN: proportion of residential land zoned for lots over 25,000 sq.ft.
  3. INDUS: proportion of non-retail business acres per town
  4. CHAS: Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)
  5. NOX: nitric oxides concentration (parts per 10 million)
  6. RM: average number of rooms per dwelling
  7. AGE: proportion of owner-occupied units built prior to 1940
  8. DIS: weighted distances to five Boston employment centres
  9. RAD: index of accessibility to radial highways
  10. TAX: full-value property-tax rate per $10,000
  11. PTRATIO: pupil-teacher ratio by town
  12. B: 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town
  13. LSTAT: % lower status of the population
  14. MEDV: Median value of owner-occupied homes in $1000's

The graph generated for housing rents in Boston is shown below

The output on console with Mean squared for training and test datasets are shown below