Practical insights

Results

9 results (published only)

• Feature engineering and preprocessing

  Avoid single mean imputation when the analysis is inferential rather than predictive

  A stakeholder wants coefficients, confidence intervals or group comparisons from data with substantial missingness.

  mediumdocumented fact

• Feature engineering and preprocessing

  Add explicit interaction terms to a linear model when the effect of one driver depends on another

  Domain knowledge says an effect varies by context, for example price sensitivity that differs between short-haul and long-haul markets.

  mediumpractitioner heuristic

• Feature engineering and preprocessing

  Prefer splines to coarse bins when a linear model needs a nonlinear single-feature effect

  You plan to cut days to departure or customer age into a few buckets so a linear model can bend.

  mediumpractitioner heuristic

• Feature engineering and preprocessing

  Compute entity history features as of the prediction timestamp with point-in-time joins

  You add aggregates such as a customer's booking count, a route's average load factor or an account's late payments to each training row.

  mediumdocumented fact

• Feature engineering and preprocessing

  Drop one dummy level for unpenalized linear regression, keep all levels for penalized models and trees

  You one-hot encode categoricals for a linear model and must decide whether to set drop='first'.

  mediumdocumented fact

• Feature engineering and preprocessing

  Replace a high-cardinality code with its descriptive attributes so new codes inherit meaning

  A model uses airport, aircraft-type or merchant codes with hundreds of levels, and new codes arrive with no history.

  mediumpractitioner heuristic

• Feature engineering and preprocessing

  Count populated cells before adding a crossed categorical feature

  You cross two or three categoricals, such as route by weekday by fare class, to give a linear model an interaction or to build a composite key.

  mediumpractitioner heuristic

• Feature engineering and preprocessing

  Replace two near-duplicate prices with one level and one gap before interpreting a linear model

  Own fare and competitor fare move together, both sit in a linear or logistic model, and their coefficients flip sign between retrains.

  mediumpractitioner heuristic

• Feature engineering and preprocessing

  Build calendar features for each timestamp that drives the outcome, such as booking date and travel date

  A booking table has both booking date and departure date, but only departure-date calendar features exist because it is the row key.

  mediumpractitioner heuristic