The Observation Theory EncyclopediaFrom TSKAboutBy kindBy chapterBy Lean fileLedgerProvenance

orthogonal concept

DefinitionOf two vectors, having dot product zero. The squared length of a sum of orthogonal vectors is the sum of the squared lengths. Chapter 0 section 0.1. Also orthonormal.
Example(1, 0) and (0, 1) are orthogonal, and the squared length of their sum is 1 + 1 = 2.
BookData Mining as Observation, draft 0.2, commit f3914f0; entry id orthogonal, kind concept.
Statusno ledger row names this entry. Corrections: none recorded.
Defining equation

Book equation 0.1.

Assumptions and scope
  • Of two vectors, having dot product zero. The relation is symmetric, survives rescaling, holds between any vector and zero, the squared length of a sum of orthogonal vectors is the sum of the squared lengths, and the residual of a projection is orthogonal to the direction projected on.
  • A linear classifier’s nuisance is everything orthogonal to its weight vector, and the eigenvectors of a symmetric matrix with distinct eigenvalues are orthogonal, so the read subspace and the nuisance split every row.
Prior artnone recorded
Evidencelean/DataMiningAsObservation/Orthogonal.lean
Reviewednot yet reviewed; generated 2026-09-10 from records at the commits on the provenance page.
uvθ
Dot product zero.

Equation

Book equation 0.1.

\[x\cdot y=\sum_{i=1}^{d}x_i y_i,\qquad \|x\|=\sqrt{x\cdot x},\qquad \cos\theta=\frac{x\cdot y}{\|x\|\,\|y\|}.\]

Conditions

Conditions are curated in entries.toml rather than read from a record.

Ledger

none

First stated

Chapter 0 section 0.1 and section 0.2 of Data Mining as Observation.

Measurements

none

Failures and corrections

none

Invariance envelope

none declared

Machine checked

lean/DataMiningAsObservation/Orthogonal.lean, theorems orth_symm, pythagoras, orth_smul, orth_zero, residual_orth, at observation-data-mining f3914f0; what the check covers is stated in the book’s appendix C.

Used in

Data Mining as Observation primer L, chapters 0, 3, 4, 6, 9, 11, 12.

Related

dot product; projection; eigenvalue, eigenvector; nuisance; read subspace.

See also

Book equations stated beside the entry’s terms, not defining it: 0.3, 0.9.

Ledger rows that cite the entry’s records without naming it: OT-7.

Sources-table rows that share a record with the entry without naming it: chapter 2 section 2.2.

Status

Generated 2026-09-10 by encyclopedia/generate.py; book at observation-data-mining f3914f0; the commit of every record is listed in the encyclopedia’s provenance.

← operating pointorthogonal matrix →