An educational crypto, finance, and AI vocabulary puzzle about wallet authorization, bond terms, classification metrics, and data processing.
Wallet Permissions
These terms describe spending permissions, their removal, and shared authorization.
Token AllowanceApproval RevocationMultisig ThresholdSession Key - Token Allowance: A token allowance is the amount a spender is permitted to transfer on behalf of a token owner.
- Approval Revocation: Approval revocation removes a previously granted token spending permission.
- Multisig Threshold: A multisig threshold specifies how many authorized signers must approve an action.
- Session Key: A session key authorizes a restricted set of wallet actions for a defined session or period.
Bond Basics
These terms describe principal, scheduled interest, repayment dates, and bond pricing conventions.
Face ValueCoupon RateMaturity DateClean Price
- Face Value: Face value is the stated principal amount of a bond, typically repayable at maturity.
- Coupon Rate: The coupon rate expresses scheduled annual interest as a percentage of a bond's face value.
- Maturity Date: The maturity date is the date when the bond principal is scheduled to be repaid.
- Clean Price: A clean price is a quoted bond price that excludes accrued interest.
Model Evaluation
These terms distinguish correct positive predictions, recovered positives, combined scores, and error counts.
PrecisionRecallF1 ScoreConfusion Matrix
- Precision: Precision is the fraction of predicted positive cases that are actually positive.
- Recall: Recall is the fraction of actual positive cases that a classifier correctly identifies.
- F1 Score: The F1 score combines precision and recall using their harmonic mean.
- Confusion Matrix: A confusion matrix counts predictions by their predicted class and actual class.
Data Pipelines
These terms cover collecting records, reshaping fields, scheduled batches, and continuous processing.
Data IngestionData TransformationBatch ProcessingStream Processing
- Data Ingestion: Data ingestion brings records from source systems into a destination for storage or processing.
- Data Transformation: Data transformation converts records into a structure or representation suitable for downstream use.
- Batch Processing: Batch processing handles a collected group of records as one scheduled or bounded job.
- Stream Processing: Stream processing handles an ongoing flow of events as they arrive.