ANTAVIRA Predictive Modeling Automation Platform

PREDICTIVE

MODELING

AUTOMATION

Platform

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CREATE FORECASTING MODELS online, fast and easy

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Concept

Solution that will change the industry

ANTAVIRA helps to build forecasting
models faster and easier. It reduces the time
spent on manual work and result computation

ANTAVIRA is suitable for data-scientists
of any level. Every professional can find
useful functionality from the system

ANTAVIRA allows you to make
up to 1,000 statistical models
simultaneously for different targets using a
large number of predictors without
repeating the same actions

ANTAVIRA combines the
tools used at each modeling step from
sampling to models staking. Each tool can be
used in conjunction with others, or separately

Benefits

Designed to become an undouptable necessity

EARN MORE MONEY

ANTAVIRA reduces building time of a good quality model GINI>0.5 from 15 working days to 2 working days.

Make more models at higher quality to get better paid

SAVE TIME

ANTAVIRA automates modeling process from samples preparation to models staking. No need to repeat set of actions unless a good model is created.

Decrease time of manual work and results computation by 60%

MAKE MORE MODELS

ANTAVIRA creates a large number of statistical models for different target variables using a large number of predictors simultaneously.

Launch more modeling experiments to get better result

INCREASE QUALITY

ANTAVIRA maximizes prediction power on each step of modeling and controls over-fitting by using included AI mode.

Increase prediction power, get better AUC, GINI, KS and avoid over-fitting

Tools

Features and Functions

SAMPLE PREPARATION

Step №1

MODELING

Step №2

ENSEMBLER MODELING

Step №3

Each module can be used separately as well as in modeling chain

Assembler

Assembles sample [variables] with sample [targets] and makes samples [variables+targets]. Number of samples [variables+targets] is equal to number of targets
Splitter

Splits samples [variables+targets] into t raining and testing samples. Where are 3 methods to split: Percent ratio; Timeline; Cross-validation
Binning

Bins every variable in every training sample using AI algorithm to maximize prediction power and avoid overfitting

Correlation

Measures correlation V-Kramer and chooses most predicable variable in every training sample using AI algorithm
Modeling

Creates set of models snd picks best one as a final result for each sample using AI algorithm
Score Calculation

Calculates scores for chosen models for any sample provided or samles from modeling chain

Model Stacking

Chooses best ensembling target, creates setof meta-models basedon models scores and picks best oneas a final result by using our innovative methods and AI algorithm
Final Score Calculation

Calculates final scores of any chosen meta-models for any sample provided or samples from modeling chain

Price

We provide free access
to Beta version of Antavira

in return on your comments
after 15 days of use

Our experience