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devtoolsentity · corroborated across sources

quantregforest

for r developers, data scientists

Steady

16

signal score

as of 5d ago

1

live items

Steady

7-day est. ~11

stackoverflow

Why this scored 16

every term, weighted
Velocity+0.0 / 40 max

Its fastest-moving item, measured against the pace of its own source

Acceleration+12.0 / 25 max

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25 max

How many independent communities its own items come from

Recency+5.9 / 10 max

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty2.2 / 30 max

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite15.7

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Outlook

low confidence · estimate, not a guarantee

7-day

~11

range 023

14-day

~7

range 021

30-day

~0

range 015

Signal history

7-day window (free)

— — projected trajectory (estimate, not a guarantee)

The evidence

The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.

  1. 114

    Use "terra::predict" with a "quantregForest" model and get the standard deviation of predictions

    Shows how to compute prediction intervals using terra::predict with quantregForest in R. — for r developers, data scientists

    stackoverflowdevtoolsSteady11d ago