Package space.kscience.kmath.optimization
Types
FunctionOptimization
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class FunctionOptimization<T>(features: FeatureSet<OptimizationFeature>, expression: DifferentiableExpression<T>) : OptimizationProblem<T>
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FunctionOptimizationBuilder
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class FunctionOptimizationBuilder<T>(expression: DifferentiableExpression<T>) : OptimizationBuilder<T, FunctionOptimization<T>>
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FunctionOptimizationTarget
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enum FunctionOptimizationTarget : Enum<FunctionOptimizationTarget> , OptimizationFeature
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OptimizationBuilder
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OptimizationCovariance
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class OptimizationCovariance<T>(covariance: Matrix<T>) : OptimizationFeature
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OptimizationFeature
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OptimizationLog
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class OptimizationLog(loggable: Loggable) : Loggable, OptimizationFeature
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OptimizationParameters
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class OptimizationParameters(symbols: List<Symbol>) : OptimizationFeature
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OptimizationPrior
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interface OptimizationPrior<T> : OptimizationFeature, DifferentiableExpression<T>
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OptimizationProblem
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OptimizationResult
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open class OptimizationResult<T>(point: Map<Symbol, T>) : OptimizationFeature
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OptimizationStartPoint
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open class OptimizationStartPoint<T>(point: Map<Symbol, T>) : OptimizationFeature
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OptimizationValue
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PointToCurveDistance
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PointWeight
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QowOptimizer
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QowRuns
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XYFit
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class XYFit(data: XYColumnarData<Double, Double, Double>, model: DifferentiableExpression<Double>, features: FeatureSet<OptimizationFeature>, pointToCurveDistance: PointToCurveDistance, pointWeight: PointWeight, xSymbol: Symbol) : OptimizationProblem<Double>
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XYOptimizationBuilder
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class XYOptimizationBuilder(data: XYColumnarData<Double, Double, Double>, model: DifferentiableExpression<Double>) : OptimizationBuilder<Double, XYFit>
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Functions
fitWith
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suspend fun <I : Any, A : ExtendedField<I>, ExpressionAlgebra<Double, I>> XYColumnarData<Double, Double, Double>.fitWith(optimizer: Optimizer<Double, XYFit>, processor: AutoDiffProcessor<Double, I, A>, startingPoint: Map<Symbol, Double>, vararg features: OptimizationFeature = emptyArray(), xSymbol: Symbol = Symbol.x, pointToCurveDistance: PointToCurveDistance = PointToCurveDistance.byY, pointWeight: PointWeight = PointWeight.byYSigma, model: A.(I) -> I): XYFit
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FunctionOptimization
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fun <T> FunctionOptimization(expression: DifferentiableExpression<T>, builder: FunctionOptimizationBuilder<T>.() -> Unit): FunctionOptimization<T>
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getFeature
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inline fun <F : OptimizationFeature> OptimizationProblem<*>.getFeature(): F?
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maximumLogLikelihood
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suspend fun Optimizer<Double, FunctionOptimization<Double>>.maximumLogLikelihood(problem: XYFit): XYFit
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suspend fun Optimizer<Double, FunctionOptimization<Double>>.maximumLogLikelihood(data: XYColumnarData<Double, Double, Double>, model: DifferentiableExpression<Double>, builder: XYOptimizationBuilder.() -> Unit): XYFit
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optimizeWith
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suspend fun <T> DifferentiableExpression<T>.optimizeWith(optimizer: Optimizer<T, FunctionOptimization<T>>, vararg startingPoint: Pair<Symbol, T>, builder: FunctionOptimizationBuilder<T>.() -> Unit = {}): FunctionOptimization<T>
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suspend fun <T> DifferentiableExpression<T>.optimizeWith(optimizer: Optimizer<T, FunctionOptimization<T>>, startingPoint: Map<Symbol, T>, builder: FunctionOptimizationBuilder<T>.() -> Unit = {}): FunctionOptimization<T>
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suspend fun <T : Any> DifferentiableExpression<T>.optimizeWith(optimizer: Optimizer<T, FunctionOptimization<T>>, startingPoint: Map<Symbol, T>, vararg features: OptimizationFeature): FunctionOptimization<T>
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withFeature
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withFeatures
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fun <T> FunctionOptimization<T>.withFeatures(vararg newFeature: OptimizationFeature): FunctionOptimization<T>
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XYOptimization
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fun XYOptimization(data: XYColumnarData<Double, Double, Double>, model: DifferentiableExpression<Double>, builder: XYOptimizationBuilder.() -> Unit): XYFit
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Properties
chiSquaredOrNull
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resultPoint
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resultPointOrNull
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resultValue
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resultValueOrNull
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startPoint
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