- Missing value synthesis, also known as missing imputation, is done by conditioning a distribution on known values, as in SynthesizeMissingValues.
- Missing values are typically represented by Missing[…].
- MissingValueSynthesis can be used at training time, inference time or to update the synthesizer of an existing model.
- Classify[data,…,MissingValueSynthesissynth] can be used to specify a missing synthesis method or model for training (and similarly for other training functions).
- ClassifierFunction[…][example,MissingValueSynthesissynth] can be used to temporarily overwrite the synthesis method during classifier inference (and similarly for other machine learning models).
- Classify[ClassifierFunction[…],MissingValueSynthesissynth] can be used to overwrite the internal missing synthesizer of the classifier (and similarly for other machine learning models).
- Possible settings for MissingValueSynthesis include:
Automatic automatically choose distribution method and synthesis strategy None do not use any missing synthesizer method use the specified method strategy how to synthesize from the distribution assoc specify both distribution method and synthesis strategy
- Possible settings for method include:
Automatic automatically choose the distribution method "Multinormal" use a multivariate normal (Gaussian) distribution "ContingencyTable" discretize data and store each possible probability "KernelDensityEstimation" use a kernel mixture distribution "DecisionTree" use a decision tree to compute probabilities "GaussianMixture" use a mixture of Gaussian (normal) distributions LearnedDistribution[…] use the specified distribution
- Possible settings for strategy include:
Automatic automatically choose the synthesis strategy "RandomSampling" randomly sample from the conditioned distribution "ModeFinding" attempt to find the mode of the conditioned distribution
- In the form Methodassoc, the association assoc should be of the form <|"LearningMethod"method,"EvaluationStrategy"strategy|>.
Basic Examples (2)
Predict an example with missing values using the "KernelDensityEstimation" distribution to condition values:
Provide an existing LearnedDistribution at training to use it when imputing missing values during training and later evaluations:
Specify an existing LearnedDistribution to synthesize missing values for an individual evaluation:
Wolfram Research (2021), MissingValueSynthesis, Wolfram Language function, https://reference.wolfram.com/language/ref/MissingValueSynthesis.html.
Wolfram Language. 2021. "MissingValueSynthesis." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/MissingValueSynthesis.html.
Wolfram Language. (2021). MissingValueSynthesis. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/MissingValueSynthesis.html