ANTAVIRA Predictive Modeling Automation Platform
PREDICTIVE
MODELING
Platform
Beta version
CREATE FORECASTING MODELS online, fast and easy
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
Speeds up modeling process by 30 times!

Antavira automates the modeling process: from sample preparation to model stacking

Save time by automation

Reduces routine work by 80%

Antavira reduces manual work and results calculation without quality loss

No need to repeat set of actions to create a good model

Unloads computer from calculations by 100%

Antavira does not require the installation of special software and the configuration of high-power computer. You can work just using your smart phone

Build models online anytime and anywhere!

Works on large samples of more than 20 GB!

Antavira is stable to big data workloads

Upload file with variables and wait until Antavira finishes calculation

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
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
Price

We provide free access
to Beta version of Antavira

in return on your comments
after 15 days of use

Our experience