Boston

housing values in suburbs of Boston.<ul>
<li>crim: per capita crime rate by town.</li>
<li>zn: proportion of residential land zoned for lots over 25,000 sq.ft.</li>
<li>indus: proportion of non-retail business acres per town</li>
<li>chas: Charles River dummy variable (= 1 if tract bounds)</li>
<li>nox: nitric oxides concentration (parts per 10 million)</li>
<li>rm: average number of rooms per dwelling</li>
<li>age: proportion of owner-occupied units built prior to 1940</li>
<li>dis: weighted distances to five Boston employment centres</li>
<li>rad: index of accessibility to radial highways</li>
<li>tax: full-value property-tax rate per $10,000</li>
<li>ptratio: pupil-teacher ratio by town</li>
<li>black: 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town</li>
<li>lstat: percentage of lower status of the population</li>
<li>medv: Median value of owner-occupied homes in $1000's</li>
</ul>

datasets

The natural increase in the complexity of current research experiments and data demands better tools to enhance productivity in Data Analytics. The package is a framework designed to address the modern challenges in data analytics workflows. The package is inspired by Experiment Line concepts. It aims to provide seamless support for users in developing their data mining workflows by offering a uniform data model and method API. It enables the integration of various data mining activities, including data preprocessing, classification, regression, clustering, and time series prediction. It also offers options for hyper-parameter tuning and supports integration with existing libraries and languages. Overall, the package provides researchers with a comprehensive set of functionalities for data science, promoting ease of use, extensibility, and integration with various tools and libraries. Information on Experiment Line is based on Ogasawara et al. (2009) <doi:10.1007/978-3-642-02279-1_20>.

Boston: Boston Housing Data (Regression)

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