LabelledCategorical<'Label> (FSharp.Stats) | FSharp.Stats

FSharp.Stats

LabelledCategorical<'Label> Type

Namespace: FSharp.Stats.Distributions.Discrete
Assembly: FSharp.Stats.dll
Base Type: obj

A wrapper around the Categorical distribution that associates each probability with a custom label of type 'Label.

Constructors

Constructor	Description
`LabelledCategorical(labels, probs)` Full Usage: `LabelledCategorical(labels, probs)` Parameters: labels : `'Label[]` - An array of labels for each category (must be unique). probs : `float[]` - An array of probabilities for each label (must sum to 1). Returns: `LabelledCategorical<'Label>`	Initializes a new instance of the LabelledCategorical distribution using label-probability pairs. labels : `'Label[]` An array of labels for each category (must be unique). probs : `float[]` An array of probabilities for each label (must sum to 1). Returns: `LabelledCategorical<'Label>`

Instance members

Instance member	Description
`this.CDF` Full Usage: `this.CDF` Parameters: label : `'Label` - The label to evaluate the cumulative probability up to. Returns: `float` The cumulative probability.	Returns the cumulative probability up to and including the given label. label : `'Label` The label to evaluate the cumulative probability up to. Returns: `float` The cumulative probability.
`this.Labels` Full Usage: `this.Labels` Returns: `'Label[]`	Gets the array of category labels. Returns: `'Label[]`
`this.MeanLabel` Full Usage: `this.MeanLabel` Returns: `'Label` The label whose index is closest to the mean.	Returns the label closest to the expected (mean) index of the distribution. Returns: `'Label` The label whose index is closest to the mean.
`this.PMF` Full Usage: `this.PMF` Parameters: label : `'Label` - The label to query. Returns: `float` The probability associated with the label, or 0.0 if the label is not found.	Returns the probability of a given label. label : `'Label` The label to query. Returns: `float` The probability associated with the label, or 0.0 if the label is not found.
`this.Probabilities` Full Usage: `this.Probabilities` Returns: `float[]`	Gets the array of probabilities associated with the labels. Returns: `float[]`
`this.Sample` Full Usage: `this.Sample` Returns: `'Label` A label corresponding to a sampled category.	Draws a random sample from the distribution and returns the sampled label. Returns: `'Label` A label corresponding to a sampled category.
`this.Support` Full Usage: `this.Support` Returns: `'Label[]`	Returns the array of labels (support of the distribution). Returns: `'Label[]`

Static members

Static member	Description
`LabelledCategorical.Estimate(labels) (counts)` Full Usage: `LabelledCategorical.Estimate(labels) (counts)` Parameters: labels : `'Label[]` - An array of labels. counts : `int[]` - An array of counts corresponding to each label. Returns: `LabelledCategorical<'Label>` A new LabelledCategorical distribution.	Estimates a distribution from labels and counts (frequencies). labels : `'Label[]` An array of labels. counts : `int[]` An array of counts corresponding to each label. Returns: `LabelledCategorical<'Label>` A new LabelledCategorical distribution.
`LabelledCategorical.Fit(observations)` Full Usage: `LabelledCategorical.Fit(observations)` Parameters: observations : `'Label[]` - An array of observed labels. Returns: `LabelledCategorical<'Label>` A new LabelledCategorical distribution with probabilities estimated from observed frequencies.	Fits a LabelledCategorical distribution from a set of labeled observations. observations : `'Label[]` An array of observed labels. Returns: `LabelledCategorical<'Label>` A new LabelledCategorical distribution with probabilities estimated from observed frequencies.
`LabelledCategorical.FromCdfUnnormalized(labels, cdf)` Full Usage: `LabelledCategorical.FromCdfUnnormalized(labels, cdf)` Parameters: labels : `'Label[]` - Labels corresponding to cumulative weights. cdf : `float[]` - Unnormalized cumulative weights (must be increasing). Returns: `LabelledCategorical<'Label>` A normalized LabelledCategorical distribution.	Initializes a LabelledCategorical distribution from labels and a cumulative unnormalized weight vector. labels : `'Label[]` Labels corresponding to cumulative weights. cdf : `float[]` Unnormalized cumulative weights (must be increasing). Returns: `LabelledCategorical<'Label>` A normalized LabelledCategorical distribution.