ANTAVIRA Predictive Modeling Automation Platform
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CREATE FORECASTING MODELS online, fast and easy
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
Designed to become an undouptable necessity

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


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%


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


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

Features and Functions
Step №1
Step №2
Step №3
Each module can be used separately as well as in modeling chain
Each module can be used separately as well as in modeling chain
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
  • Sample preparation
  • Modeling
  • Ensemble modeling

We provide free access
to Beta version of Antavira

in return on your comments
after 15 days of use

Our experience