Linear Discriminant Score Calculator
Score a two-dimensional observation against two Gaussian classes with a common positive-definite covariance.
YOUR CALCULATION
Result
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Calculation steps
Work through one step at a time or reveal the complete calculation. The steps use your current inputs.
How to calculate
Validate the common covariance by Cholesky factorization, then evaluate the Gaussian discriminant difference.
Log odds=(μ1−μ0)ᵀΣ⁻¹x−(μ1ᵀΣ⁻¹μ1−μ0ᵀΣ⁻¹μ0)/2+log prior odds
Worked example
Identity covariance, means(0,0)/(2,2), equal priors and query(1,1) give equal scores.
Assumptions and input details
Two entered Gaussian models with equal covariance; no training-data covariance estimation, accuracy assessment or causal inference. Very ill-conditioned covariance is rejected.
Using this calculator
Can I enter my own problem?
Yes. Replace the example values with your own inputs. The result, calculation steps, tables and applicable diagrams update from those inputs. Blank or invalid values clear the result; example values are never silently substituted for missing inputs.
Are the results exact?
Results use floating-point arithmetic and displayed rounding. Read the formula, assumptions and any stated data precision before interpreting the result.
Is my input uploaded?
The calculation runs in your browser. No account, file upload or external AI service is required. Inputs are not saved between page reloads.
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