VA-ML
Vector Algorithmics · Machine Learning Platform
Overview
API Online
admin
Confusion Matrix i
TP — TAKE + Win
FP — TAKE + Loss
TN — AVOID + Loss saved
FN — AVOID + Win missed
Feature Importance (SHAP) i
By Direction i
Validation Stability i
NQ CME
Timeframe
1m
5m
15m
30m
1h
Overlays
Oscillators
Saved Layouts
NQ O H L C Vol
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Powered by TradingView · Databento CME

Signals

Automated prediction · market conditions are read-only · sourced from Databento · generated daily at market open

Market Conditions read-only · Databento
▶ Show
Today's Signal
LONG ▲
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SHORT ▼
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Signal History & Model P&L
auto-populated from paper trading
DateLongShortModel P&LLabel
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Launch Training

Configure training mode, select a strategy, and submit a new training job

Training Mode
Manual
Auto-SHAP
Auto-Search
Trains with the GFPB Approach A feature set. Select which indicators to include below.
Feature Set — GFPB Approach A
Select indicators to include in this training run:
13 / 13 selected
Strategy
Queued…
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Training History

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All Runs
Learning Signals — FN Trades i
AFML Meta-labeling (Ch. 3 — López de Prado): The base strategy is the primary model; the ML classifier is the secondary meta-labeler. FN trades are where the primary was correct but the secondary filtered it out — highest-value data points for retraining.
Strategies
Click to view details & config
Select a strategy to view details

Playback

Simulate strategy execution on historical days using tick data from S3

Setup
Strategy
Date Range
Fork to Custom Variant
Creates a new instance from base
Name it after what you are changing — instrument, days, targets...
Journals and runs are NOT inherited. This variant starts fresh and accumulates its own execution data independently from the base.
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TP
FP
TN saved
FN missed

Market Data

Bar files shared across all strategies · sourced from Databento · universal input for training

Glossary

Term definitions from the platform