Tagged “tabular”

4 posts.

All Model Architecture19 Training & Alignment22 Inference & Serving18 Agents & Orchestration11 Reasoning & Evaluation26 Safety, Security & Governance7 Platforms & Practice20

Reasoning & Evaluation 24 min

Inside Gradient-Boosted Trees: The Engineering That Made XGBoost, LightGBM and CatBoost Win Tabular ML

XGBoost, LightGBM and CatBoost minimise the same objective with the same kind of tree. What separates them is bookkeeping: XGBoost turned two sums of derivatives into a split score, LightGBM made those sums cheap, and CatBoost ma…

trees-and-ensembles gradient-boosting xgboost tabular ∑ ◫

Reasoning & Evaluation 27 min

The Last Undefeated Baseline: Why Gradient-Boosted Trees Still Beat Deep Learning on Tabular Data

Deep learning took images in three years and text in five. It has been attacking tabular data since 2016 and still has not won. The reason is not compute or architecture; it is three specific inductive biases that make a tree the…

tabular gradient-boosting deep-learning xgboost ∑ ◫

Reasoning & Evaluation 24 min

What a Feature Attribution Can and Cannot Tell You: SHAP, LIME and the Explanation Gap

Add a column the model never reads and SHAP can hand it more than a quarter of the credit for a decision. That is not a library bug: a Shapley attribution answers a question you chose, often without noticing, and a 2024 PNAS resu…

transparency-and-documentation interpretability responsible-ai causal-inference ∑ ◫

Reasoning & Evaluation 3 min

What the bake-off taught us: classical ML is not dead, it is just under-attended

We pitted twelve sklearn algorithms head-to-head on a tabular dataset. The winner was not the most expensive one. It was not the most modern one. It was the one whose assumptions matched the data.

machine-learning tabular benchmarks evaluation