Boston_housing

This is a modified version of the famous Boston housing data set. This data set includes rows 4:209 and 212:506. The data here is complete except for the data use to make New_Boston.
The data first appeared in a paper by David Harrison, Jr. and Daniel L. Rubenfeld, Hedonic housing Prices and the demand for clean air. This was published in March, 1978.
Journal of Environmental Economics and Management 5(1):81-102. The descriptions below are quoted from the original paper:<dl>
<dt>crim</dt>
<dd>Crime rate by town. Original data in 1970 FBI data</dd><dt>zn</dt>
<dd>Proportion of a town's residential land zoned for lots greater than 25,000 square feet</dd><dt>indus</dt>
<dd>Proportional non-retail business per town</dd><dt>chas</dt>
<dd>Captures the amenities of a riverside location and thus should be positive</dd><dt>nox</dt>
<dd>Nitrogen oxygen concentrations in part per hundred million</dd><dt>rm</dt>
<dd>Average number of rooms in owner units</dd><dt>age</dt>
<dd>Proportion of owner units built prior to 1940</dd><dt>dis</dt>
<dd>Weighted distances to five employment centers in the Boston region</dd><dt>rad</dt>
<dd>Index of accessibility to radial highways</dd><dt>tax</dt>
<dd>Full property value tax rate ($/$10,000)</dd><dt>ptratio</dt>
<dd>Pupil-teacher ratio by town school district</dd><dt>black</dt>
<dd>Black proportion of population</dd><dt>lstat</dt>
<dd>Proportion of population that is lower status (proportion of adults without some high school education and proportion of male workers classified as laborers)</dd><dt>medv</dt>
<dd>Median value of owner occupied homes, from the 1970 United States census</dd>
</dl>

datasets

Automatically runs 23 individual models and 17 ensembles on numeric data. The package automatically returns complete results on all 40 models,
25 charts, multiple tables. The user simply provides the data, and answers a few questions (for example, how many times would you like to resample the data).
From there the package randomly splits the data into train, test and validation sets, builds models on the training data, makes predictions on the test and validation sets,
measures root mean squared error (RMSE), removes features above a user-set level of Variance Inflation Factor, and has several optional features including scaling
all numeric data, four different ways to handle strings in the data. Perhaps the most significant feature is the package's ability to make predictions
using the 40 pre trained models on totally new (untrained) data if the user selects that feature. This feature alone represents a very effective solution
to the issue of reproducibility of models in data science. The package can also randomly resample the data as many times as the user sets, thus giving more
accurate results than a single run. The graphs provide many results that are not typically found. For example, the package automatically calculates the Kolmogorov-Smirnov
test for each of the 40 models and plots a bar chart of the results, a bias bar chart of each of the 40 models, as well as several plots for exploratory data
analysis (automatic histograms of the numeric data, automatic histograms of the numeric data). The package also automatically creates a summary report
that can be both sorted and searched for each of the 40 models, including RMSE, bias, train RMSE, test RMSE, validation RMSE, overfitting and duration.
The best results on the holdout data typically beat the best results in data science competitions and published results for the same data set.

Russ Conte

NumericEnsembles

Automatically Runs 23 Individual and 17 Ensembles of Models

Boston_housing function

An object of class <code>data.frame</code> with 501 rows and 14 columns.

Format

This is a modified version of the famous Boston housing data set. This data set includes rows 4:209 and 212:506. The data here is complete except for the data use to make New_Boston.
The data first appeared in a paper by David Harrison, Jr. and Daniel L. Rubenfeld, Hedonic housing Prices and the demand for clean air. This was published in March, 1978.
Journal of Environmental Economics and Management 5(1):81-102. The descriptions below are quoted from the original paper:<dl>
<dt>crim</dt>
<dd>Crime rate by town. Original data in 1970 FBI data</dd>

<dt>zn</dt>
<dd>Proportion of a town's residential land zoned for lots greater than 25,000 square feet</dd>

<dt>indus</dt>
<dd>Proportional non-retail business per town</dd>

<dt>chas</dt>
<dd>Captures the amenities of a riverside location and thus should be positive</dd>

<dt>nox</dt>
<dd>Nitrogen oxygen concentrations in part per hundred million</dd>

<dt>rm</dt>
<dd>Average number of rooms in owner units</dd>

<dt>age</dt>
<dd>Proportion of owner units built prior to 1940</dd>

<dt>dis</dt>
<dd>Weighted distances to five employment centers in the Boston region</dd>

<dt>rad</dt>
<dd>Index of accessibility to radial highways</dd>

<dt>tax</dt>
<dd>Full property value tax rate ($/$10,000)</dd>

<dt>ptratio</dt>
<dd>Pupil-teacher ratio by town school district</dd>

<dt>black</dt>
<dd>Black proportion of population</dd>

<dt>lstat</dt>
<dd>Proportion of population that is lower status (proportion of adults without some high school education and proportion of male workers classified as laborers)</dd>

<dt>medv</dt>
<dd>Median value of owner occupied homes, from the 1970 United States census</dd>


</dl>

Boston_housing: Boston_housing data

Description

Usage

Arguments

Format