Abstract:
In this research, we investigated business development by using the performance of regression
algorithms namely Simple Linear Regression, Multiple Linear Regression and Polynomial
Regression for predicting the number of Investment growth in business. We utilized the
information of two years of speculation of foundation to anticipate the quantity of legitimate
interest in every voting public. Foreseeing pace of venture from the aggregate sum of speculation
is extremely vital for foundation Data Analytics. From past venture of foundation and year
esteems, we can foresee speculation development of benefit threw and from those qualities, we
can without much of a stretch infer speculation turnout, which is important for establishment
partners. A high or low contribute turnout means that how much development benefit and stream
a sum in an establishment. We used excel to carry out the all the research work such as data
preprocessing, feature selection, data analysis and evaluation. We found that Multiple Linear
Regression is the best performer among Simple Linear Regression and Polynomial Regression
both in terms of In-Sample and Out-of-Sample evaluation. We reached to the conclusion that
multiple attributes can contribute to less error prone prediction.
