Predictive Analytics with INTELLIBOT
Predictive analytics is leveraged to create predictions about unknown future actions. It uses numerous techniques, such as statistical algorithms, data mining, statistics, modelling, machine learning and AI, to evaluate current data and make forecasts about the future. It aims to identify the possibility of future results based on the available historical data. The goal is therefore to go past what has occurred to provide the finest assessment of what will occur.
In business, predictive models engages patterns found in past and transactional data to recognize risks and opportunities. Variables capture relationships among many factors to allow valuation of risk or potentials related with a set of conditions.
The primary objective in an analytics project is to quickly demonstrate the analysed data’s effectiveness. By elevating their data quality, organizations could complete their projects and achieve their first data results. These data results could then be used to mature and develop more features and continuously improve results and model outputs.
Who Uses it ?
Growing organisations use Predictive Awareness to identify concealed opportunities and uncover hidden risks buried within the organizations past data. By leveraging Predictive Analytics and exposing the capabilities to everyone within their organization empowerment to make the right calls at the right moment and
transform their future into a greater success is eminent.
Does your organisation also leverage the power of Predictive Analytics?
Industry Specific Use Cases:
Banking & Financial Services
Governments & the Public Sector
Oil, Gas & Utilities
INTELLIBOT Predictive Analytics Platform
Intellibot is very excited to introduce Intellibot Predictive Analytics & Intellibot Recommendation Engine as a very significant addition to its current machine learning offerings.
These functionalities are an integral part of the Intellibot platform and do not require connectivity to external cloud environments.
Intellibot Predictive Analytics capability to consume PMML Models created using multiple frameworks such as R, IBM SPSS, TensorFlow, AWS SageMaker and more, enabling organizations to bring together process, people, technology and information into a value network and provide extensive selection of data and decision-making capability.
How simple is it?
Just configure the PMML file path and Intellibot Predictive Analytics in sync with the Intellibot Recommendation Engine will dynamically create simple Data Input and Output Ports for the dependant and independent variables distinctly.
Machine Learning algorithms currently supported by Intellibot :
• Associative Rule
• Cox Regression
• General Regression
• Multinomial Regression
• Naive Bayes
• Neural Networks
• Random Forest
• Support Vector Machine
• Tree Model
(Intellibot Community Version)