Demand forecasting ablation
Compare removals from a demand forecast, from seasonality inputs to regional pooling, against its fixed baseline; illustrative deltas are not measured performance or causal evidence. Typed FlowScript for machine-learning evaluation. Keywords: ablation, benchmark, evaluation, model comparison.
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// Compare removals from a demand forecast, from seasonality inputs to regional pooling, against its fixed baseline; illustrative deltas are not measured performance or causal evidence.
// Synthetic worked example: all entities, schedules and measurements are illustrative.
// Every string below is EXAMPLE text from a fictional model: replace it.
// Replace assumptions and inputs before applying this model to actual work.
model baseline_model {
title: "Illustrative Demand forecast"
params: 12000000
family: "Research prototype"
}
dataset evaluation_set {
title: "Synthetic Time-separated evaluation window"
n: 500
split: "held-out"
}
eval baseline_eval {
model: baseline_model
dataset: evaluation_set
metric: "Illustrative bounded quality score; higher is better"
score: 0.82
}
ablation variant_0 {
base: baseline_eval
delta: -0.045
change: "Remove seasonality inputs"
}
ablation variant_1 {
base: baseline_eval
delta: -0.02
change: "Remove holiday indicator"
}
ablation variant_2 {
base: baseline_eval
delta: -0.09
change: "Remove lagged demand"
}
ablation variant_3 {
base: baseline_eval
delta: -0.06
change: "Remove stockout correction"
}
ablation variant_4 {
base: baseline_eval
delta: -0.035
change: "Remove regional pooling"
}
view variants: ablation_table(baseline_eval)