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Predicting Kilowatt Consumption

Whenever past performance is indicative of future results, predictive modeling is prescient. Such is the case with electrical bills. Twenty-two months worth of electrical bills for a four bedroom, two bath apartment of a 1500 square foot duplex in the Lincoln, Nebraska area were submitted by residents. The following billing-period statistics were abstracted from each electrical bill: kWh, total kilowatt hour usage, avg_kWh_per_day, average kilowatt hour usage per day, avg_high, average high temperature, and avg_low, average low temperature.

Random Forests Outperform Simple Regression on Solubility Data

Solubility can be defined as the propensity of a solid, liquid, or gaseous quantity (solute) to dissolve in another substance (solvent). Among many factors, temperature, pH, and pressure, and entropy of mixing all impact solubility. (Loudon, Parise 2016) Solvents can be classified as either protic or aprotic, polar or apolar, and donor or nondonor. (Loudon, Parise 2016) The specifics, illustrated by the solubility data set from Applied Predictive Modeling, are beyond the scope of this paper.