Data Analytics is an emerging area for analyzing various kinds of data.
Predictive analytics is one of the essential techniques under data analytics, which is
used to predict the data gainfully with machine learning algorithms. There are various
types of machine learning algorithms available coming under the umbrella of
supervised and unsupervised methods, which give suitable and better performance on
data along with various analytics methods. Regression is a useful and familiar
statistical method to analyze the data fruitfully. Analysis of medical data is most
helpful to both patients as well as the experts to identify and rectify the problems to
overcome future problems. Autism is a brain nerve disorder that is increasing in the
children by birth due to some most chemical food items and some side effects of other
treatments and various causes. Logistic Regression is one of the supervised machine
learning algorithms which can operate the dataset of binary data that is 0 and 1.
Agriculture is one of the primary data which should be considered and analyzed for
saving the future generation. Rainfall is a more elementary requirement for the global
level and also countries which are having backbone as agriculture. Due to the
topography, geography, political, and other socio-economic factors, agriculture is
affected. Thus, the demand for food and food products is intensifying. Especially crop
production is depending upon the rainfall, so, prediction of rainfall and crop
production is essential. Analysis of social crime relevant data is indispensable because
analytics can produce better results, which leads to reducing the crime level.
Unexpectedly child abuse is increasing day by day in India. Linear regression is the
supervised machine learning algorithm to predict quantitative data efficiently.
This chapter is roofed with various datasets such as autism from medical, rainfall, and
crop production from agriculture and child abuse data from the social domain.
Predictive analytics is one of the analytical models which predict the data for the
future era. Supervised machine learning algorithms such as linear and logistic
regression will be used to perform the prediction.
Keywords: Data analytics, Exponential distribution, Inomial distribution, Linear
regression, Logistic regression, Machine learning, Normal distribution, Prediction
analytics.
