Top Open-Source Tools for Predictive Modeling

What’s predictive modeling?

It’s a procedure for the creation of a statistical model for the prediction of future behavior. It’s involved more with the prediction, forecasting, and seeing the future trends and probabilities. All of it means, the analysis is done for the prediction of something and it’s called predictive analysis.

For a retail company, the basic knowledge of, let’s say demographics, geography, gender, and predilections can open huge doors with a great number of permutations and combinations in which people can be shown the call to action prompt.

There are different features which are used to describe the kind of predictive model that is being used. The key features are:

• Predictors

• The predicted outcome

• How predictors help with the creation of outcome

It’s surprising how predictive analytics started with the spam filtering system. Today, it has come to be leveraged in a lot of industries in different ways for various purposes. It is increasingly being used in disaster recovery, change management, customer relationship management, meteorology, and security management.

Business depends a lot on decisions. Bad decisions can result in drastic losses while good ones will result in successes. With predictive analytics, time-consuming processes are eliminated. It diagnoses business with ultimate precision.

There are a number of tools available as open source in the market which can be leveraged for predictive analysis. They are a part of undergoing a big data analyst certification. Here’s the list of top ones, which you must also check in before committing to data analytics certifications. Take a look:

R: If you have anything to do with graphics and statistical computing, R is your go-to software programming language. What’s more? It’s free. A big data analyst certification is sure to teach you some tricks of R as it is hugely sought by many companies to hire their analysts.

RapidMiner: It is a software platform. It can be leveraged for the creation of an integrated environment for business analytics, predictive analytics, text mining, data mining, and machine learning.

Apache Mahout: It’s a project to create and develop free implementation of scalable machine learning algorithms, no matter whether they are scalable or not. It primarily deals with collaborative filtering, classification, and clustering.

GNU Octave: Another in the list of open-source tools. It is a programming language for high-level numerical computations.

Scikit-learn: It is a machine learning library for all sorts of details about Python programming language.

Orange: It’s a component-based software suite meant for machine learning and data mining. Talking of components, they include pre-processing of data, modeling, evaluation of models, and techniques for exploration.

Weka: It’s one of the top suites of machine learning software. Created at the University of Waikato, located in New Zealand, the tool uses Java language. The tool has a collection of algorithms and visualization tools for predictive modeling and analysis.

OpenNN: It’s a software library. The best part about this is- its ability to learn from mathematical models as well as datasets. Not limited to this, the software can be leveraged to solve various problems related to pattern recognition.

KNIME: This open-source tool is a software library. What it does is an integration of different components for data mining and machine learning.

The demand for predictive analysis has increased the transformative power of digital disruption. It has armed companies with the production of data which when used effectively can give them the power of insights about the future. For people considering a career in future prediction for companies, the market offers great data analytics certifications. Even companies want a big data analytics certification before hiring an individual.