boston

boston, a keras code which reads the Boston housing dataset using internal data functions, rather than referencing the built-in keras dataset, and applies regression to predict housing prices

Licensing:

The information on this web page is distributed under the MIT license.

Related Programs:

boston_housing, a dataset which stores training and test data about housing prices in Boston. This dataset is also available as a builtin dataset in keras.

boston_housing, a keras code which sets up a neural network to apply regression to predict housing prices, based on the Boston housing dataset.

boston_housing_external, a keras code which sets up a neural network to apply regression to predict housing prices, based on the Boston housing dataset, which is read from an external file, rather than by accessing the keras dataset service.

Author:

Original keras version by Francois Chollet; This version by John Burkardt.

Reference:

• D A Belsley, E Kuh, R E Welsch,
  Regression Diagnostics: Identifying Influential Data and Sources of Collinearity,
  New York, Wiley, 1980.
• Francois Chollet,
  Deep Learning with Python,
  Manning, 2018,
  ISBN: 9781617294433.
• D Harrison, D L Rubinfeld,
  Hedonic prices and the demand for clean air,
  J. Environ. Economics and Management,
  Volume 5, pages 81–102, 1978.

Source Code:

• boston.py, the script.
• boston.sh, runs the script.
• boston.txt, the output file.

• boston_validation_mae.png, the validation MAE curve.
• boston_validation_mae_smoothed.png, the validation MAE curve, after dropping first 10 points and smoothing the rest.