Cloud AutoML V1beta1 API - Class Google::Cloud::AutoML::V1beta1::Float64Stats (v0.7.0)

Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::Float64Stats.

The data statistics of a series of FLOAT64 values.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#histogram_buckets

def histogram_buckets() -> ::Array<::Google::Cloud::AutoML::V1beta1::Float64Stats::HistogramBucket>
Returns
  • (::Array<::Google::Cloud::AutoML::V1beta1::Float64Stats::HistogramBucket>) — Histogram buckets of the data series. Sorted by the min value of the bucket, ascendingly, and the number of the buckets is dynamically generated. The buckets are non-overlapping and completely cover whole FLOAT64 range with min of first bucket being "-Infinity", and max of the last one being "Infinity".

#histogram_buckets=

def histogram_buckets=(value) -> ::Array<::Google::Cloud::AutoML::V1beta1::Float64Stats::HistogramBucket>
Parameter
  • value (::Array<::Google::Cloud::AutoML::V1beta1::Float64Stats::HistogramBucket>) — Histogram buckets of the data series. Sorted by the min value of the bucket, ascendingly, and the number of the buckets is dynamically generated. The buckets are non-overlapping and completely cover whole FLOAT64 range with min of first bucket being "-Infinity", and max of the last one being "Infinity".
Returns
  • (::Array<::Google::Cloud::AutoML::V1beta1::Float64Stats::HistogramBucket>) — Histogram buckets of the data series. Sorted by the min value of the bucket, ascendingly, and the number of the buckets is dynamically generated. The buckets are non-overlapping and completely cover whole FLOAT64 range with min of first bucket being "-Infinity", and max of the last one being "Infinity".

#mean

def mean() -> ::Float
Returns
  • (::Float) — The mean of the series.

#mean=

def mean=(value) -> ::Float
Parameter
  • value (::Float) — The mean of the series.
Returns
  • (::Float) — The mean of the series.

#quantiles

def quantiles() -> ::Array<::Float>
Returns
  • (::Array<::Float>) — Ordered from 0 to k k-quantile values of the data series of n values. The value at index i is, approximately, the i*n/k-th smallest value in the series; for i = 0 and i = k these are, respectively, the min and max values.

#quantiles=

def quantiles=(value) -> ::Array<::Float>
Parameter
  • value (::Array<::Float>) — Ordered from 0 to k k-quantile values of the data series of n values. The value at index i is, approximately, the i*n/k-th smallest value in the series; for i = 0 and i = k these are, respectively, the min and max values.
Returns
  • (::Array<::Float>) — Ordered from 0 to k k-quantile values of the data series of n values. The value at index i is, approximately, the i*n/k-th smallest value in the series; for i = 0 and i = k these are, respectively, the min and max values.

#standard_deviation

def standard_deviation() -> ::Float
Returns
  • (::Float) — The standard deviation of the series.

#standard_deviation=

def standard_deviation=(value) -> ::Float
Parameter
  • value (::Float) — The standard deviation of the series.
Returns
  • (::Float) — The standard deviation of the series.