Uplift Modeling
Estimating the causal impact of an intervention on an individual compared to control, often used for targeting marketing or product treatments.
Estimating the causal impact of an intervention on an individual compared to control, often used for targeting marketing or product treatments.
Quantifying model confidence or epistemic/aleatoric uncertainty in predictions; used for calibration, abstention, and risk‑aware decisions.
When a model is too simple to capture patterns in the data, leading to high bias and poor training and test performance.
Raw inputs without ground‑truth annotations; used in self‑supervised, unsupervised, or pretraining regimes to scale model learning.
Aggregate value of assets deposited in a protocol or chain, commonly used to gauge usage and liquidity, but sensitive to price swings and double counting.
Metric for blockchain throughput, often compared across networks; raw TPS claims can be misleading without details on security and data availability.
Rate at which a blockchain processes transactions; constrained by block size, latency, verification, and data availability bandwidth.
Pending transaction queue held by nodes before inclusion in a block; subject to fee competition, replacements, and local policy differences.
Assurance that a confirmed transaction will not be reversed; can be probabilistic (PoW) or deterministic via BFT finality gadgets or checkpoints.
Monotonic counter per account that prevents replay and orders transactions; gaps can stall later txs until missing nonces are mined or replaced.
Amount paid to compensate validators/miners for computation and inclusion; may include base fee, tip, and burn depending on the fee market design.