A C D F G H I J K L M N P R S T U V W

A

Arrow - Class in tech.v3.libs

Bindings to save/load datasets apache arrow streaming format.

C

column(Object, Object) - Static method in class tech.v3.TMD

Return the column named cname else throw exception.

columnCount(Object) - Static method in class tech.v3.TMD

Return the number of columns.

columnDef(Object, Object) - Static method in class tech.v3.TMD

Efficiently create a column definition explicitly specifying name and data.

columnDef(Object, Object, Object) - Static method in class tech.v3.TMD

Efficiently create a column definition explicitly specifying name, data, and missing.

columnDef(Object, Object, Object, Object) - Static method in class tech.v3.TMD

Efficiently create a column definition explicitly specifying name, data, missing, and metadata.

columnMap(Object, Object, IFn, Object) - Static method in class tech.v3.TMD

Map a function across 1 or more columns to produce a new column.

concatCopying(Object) - Static method in class tech.v3.TMD

Concatenate an Iterable of datasets into one dataset via copying data into one dataset.

concatInplace(Object) - Static method in class tech.v3.TMD

Concatenate an Iterable of datasets into one dataset via creating virtual buffers that index into the previous datasets.

correlationTable(Object, Object) - Static method in class tech.v3.dataset.Modelling

Return a map of column to inversely sorted from greatest to least sequence of tuples of column name, coefficient.

correlationTable(Object) - Static method in class tech.v3.dataset.Modelling

Return a map of column to inversely sorted from greatest to least sequence of tuples of column name, pearson correlation coefficient.

D

datasetSeqToParquet(Iterable, String, Object) - Static method in class tech.v3.libs.Parquet

datasetSeqToStream(Iterable, Object, Object) - Static method in class tech.v3.libs.Arrow

Save a sequence of datasets to a single stream file.

datasetToParquet(Object, String, Object) - Static method in class tech.v3.libs.Parquet

datasetToStream(Object, Object, Object) - Static method in class tech.v3.libs.Arrow

Save a dataset to apache stream format.

descriptiveStats(Object, Object) - Static method in class tech.v3.TMD

Create a dataset of the descriptive statistics of the input dataset.

descriptiveStats(Object) - Static method in class tech.v3.TMD

Create a dataset of the descriptive statistics of the input dataset.

distinct(Object) - Static method in class tech.v3.dataset.Reductions

Returns a distinct reducer produces a set of distinct values.

distinctUInt32(Object) - Static method in class tech.v3.dataset.Reductions

Returns a distinct reducer that produces a roaringbitmap of distinct values.

dropColumns(Object, Object) - Static method in class tech.v3.TMD

Drop columns by name.

dropRows(Object, Object) - Static method in class tech.v3.TMD

Drop rows by index.

F

fillRangeReplace(Object, Object, double, Object) - Static method in class tech.v3.dataset.Modelling

Expand a dataset ensuring that the difference between two successive values is less than max-span.

filter(Object, IFn) - Static method in class tech.v3.TMD

Filter a dataset.

filterColumn(Object, Object, IFn) - Static method in class tech.v3.TMD

Filter a dataset.

first(Object) - Static method in class tech.v3.dataset.Rolling

reducer that keeps the first value

fitCategorical(Object, Object, Object) - Static method in class tech.v3.dataset.Modelling

Fit an object->integer transform that takes each value and assigned an integer to it.

fitCategorical(Object, Object) - Static method in class tech.v3.dataset.Modelling

Fit an object->integer transformation.

fitMinMax(Object, Object) - Static method in class tech.v3.dataset.Modelling

Fit a bias and scale the dataset that transforms each colum to a target min-max value.

fitMinMax(Object) - Static method in class tech.v3.dataset.Modelling

Fit a minmax transformation that will transform each column to a minimum of -0.5 and a maximum of 0.5.

fitOneHot(Object, Object, Object) - Static method in class tech.v3.dataset.Modelling

Fit a transformation from a single column of categorical values to a one-hot encoded group of columns.

fitOneHot(Object, Object) - Static method in class tech.v3.dataset.Modelling

Fit a mapping from a categorical column to a group of one-hot encoded columns.

fitPCA(Object, Object) - Static method in class tech.v3.dataset.Modelling

Fit a PCA transformation on a dataset.

fitPCA(Object) - Static method in class tech.v3.dataset.Modelling

Fit a PCA transformation onto a dataset keeping 95% of the variance.

fitStdScale(Object) - Static method in class tech.v3.dataset.Modelling

Calculate per-column mean, stddev.

fixedWindow(long) - Static method in class tech.v3.dataset.Rolling

Return fixed size rolling window.

fixedWindow(long, Keyword) - Static method in class tech.v3.dataset.Rolling

Return fixed size rolling window.

fixedWindow(long, Keyword, Keyword) - Static method in class tech.v3.dataset.Rolling

Return fixed size rolling window.

G

groupBy(Object, IFn) - Static method in class tech.v3.TMD

Group a dataset returning a Map of keys to dataset.

groupByColumn(Object, Object) - Static method in class tech.v3.TMD

Group a dataset by a specific column returning a Map of keys to dataset.

groupByColumnsAgg(Iterable, Object, Map, Map) - Static method in class tech.v3.dataset.Reductions

Group a sequence of datasets by column or columns an in the process perform an aggregation.

H

head(Object) - Static method in class tech.v3.TMD

Return the first 5 rows of the dataset

head(Object, long) - Static method in class tech.v3.TMD

Return the first N rows of the dataset

I

inferenceTargetLabelMap(Object) - Static method in class tech.v3.dataset.Modelling

Return a map of val->idx for the inference target.

interpolateLOESS(Object, Object, Object, Object) - Static method in class tech.v3.dataset.Modelling

Map a LOESS-interpolation transformation onto a dataset.

interpolateLOESS(Object, Object, Object) - Static method in class tech.v3.dataset.Modelling

Perform a LOESS interpolation using the default parameters.

invertCategorical(Object, Object) - Static method in class tech.v3.dataset.Modelling

Reverse a previously transformed categorical mapping.

invertOneHot(Object, Object) - Static method in class tech.v3.dataset.Modelling

Reverse a previously transformed one-hot mapping.

isDataset(Object) - Static method in class tech.v3.TMD

Returns true if this object is a dataset.

J

join(Map, Map, Map) - Static method in class tech.v3.TMD

Perform a join operation between two datasets.

K

kFold(Object, long, Object) - Static method in class tech.v3.dataset.Modelling

Produce 2*k datasets from 1 dataset using k-fold algorithm.

kFold(Object, long) - Static method in class tech.v3.dataset.Modelling

Return k maps of the form {:test-ds :train-ds}.

L

labels(Object) - Static method in class tech.v3.dataset.Modelling

Find the inference column.

last(Object) - Static method in class tech.v3.dataset.Rolling

reducer that keeps the last value

leftJoinAsof(Object, Map, Map, Object) - Static method in class tech.v3.TMD

Perform a left join but join on nearest value as opposed to matching value.

leftJoinAsof(Object, Map, Map) - Static method in class tech.v3.TMD

M

makeDataset(Object, Map) - Static method in class tech.v3.TMD

Basic pathway to take data and get back a datasets.

makeDataset(Object) - Static method in class tech.v3.TMD

Make a dataset.

max(Object) - Static method in class tech.v3.dataset.Rolling

max reducer

mean(Object) - Static method in class tech.v3.dataset.Reductions

Returns a mean reducer that produces a mean value of an individual source column.

mean(Object) - Static method in class tech.v3.dataset.Rolling

mean reducer

min(Object) - Static method in class tech.v3.dataset.Rolling

min reducer

missing(Object) - Static method in class tech.v3.TMD

Return the missing set of a dataset or a column in the form of a RoaringBitmap.

Modelling - Class in tech.v3.dataset

Functions related to training and evaluating ML models.

N

neanderthalToDataset(Object) - Static method in class tech.v3.TMD

Convert a neanderthal matrix to a dataset such that the columns of the matrix become the columns of the dataset.

P

Parquet - Class in tech.v3.libs

Read/write parquet files.

parquetMetadata(String) - Static method in class tech.v3.libs.Parquet

parquetToDataset(String, Object) - Static method in class tech.v3.libs.Parquet

parquetToDatasetSeq(String, Object) - Static method in class tech.v3.libs.Parquet

pmapDS(Object, IFn, Object) - Static method in class tech.v3.TMD

Parallelize mapping a function from dataset->dataset across a dataset.

probabilityDistributionToLabels(Object) - Static method in class tech.v3.dataset.Modelling

Given a dataset where the column names are labels and the each row is a probabilitly distribution across the labels, produce a Buffer of labels taking the highest probability for each row to choose the label.

probCDFS(Object, Object, long) - Static method in class tech.v3.dataset.Reductions

Probabilistic CDF calculation, one for each double cdf passed in.

probCDFS(Object, Object) - Static method in class tech.v3.dataset.Reductions

Probabilistic CDF calculation, one for each double cdf passed in.

probInterquartileRange(Object, long) - Static method in class tech.v3.dataset.Reductions

Probabilistic interquartile range.

probInterquartileRange(Object) - Static method in class tech.v3.dataset.Reductions

Probabilistic interquartile range.

probMedian(Object, long) - Static method in class tech.v3.dataset.Reductions

Probabilistic median.

probMedian(Object) - Static method in class tech.v3.dataset.Reductions

Probabilistic median with default K of 128.

probPMFS(Object, Object, long) - Static method in class tech.v3.dataset.Reductions

Returns an approximation to the Probability Mass Function (PMF) of the input stream given a set of splitPoints (values).

probPMFS(Object, Object) - Static method in class tech.v3.dataset.Reductions

Returns an approximation to the Probability Mass Function (PMF) of the input stream given a set of splitPoints (values).

probQuantile(Object, double, long) - Static method in class tech.v3.dataset.Reductions

Probabilistic quantile estimation using default k of 128.

probQuantile(Object, double) - Static method in class tech.v3.dataset.Reductions

Probabilistic quantile estimation using default k of 128.

probQuantiles(Object, Object, long) - Static method in class tech.v3.dataset.Reductions

Probabilistic quantile estimation - see DoublesSketch.

probQuantiles(Object, Object) - Static method in class tech.v3.dataset.Reductions

Probabilistic quantile estimation using default k of 128.

probSetCardinality(Object, Map) - Static method in class tech.v3.dataset.Reductions

Calculate a probabilistic set cardinality for a given column based on one of three algorithms.

R

reducer(Object, IFn, IFn) - Static method in class tech.v3.dataset.Reductions

Create a custom reducer.

reducer(Object, IFn) - Static method in class tech.v3.dataset.Reductions

Create a custom reducer.

reducer(Object, IFn, Keyword) - Static method in class tech.v3.dataset.Rolling

Create a columnwise reducer.

reducer(Object, IFn) - Static method in class tech.v3.dataset.Rolling

Create a columnwise reducer eliding datatype parameter.

Reductions - Class in tech.v3.dataset

High speed grouping aggregations based on sequences of datasets.

renameColumns(Object, Map) - Static method in class tech.v3.TMD

Rename columns providing a map of oldname to newname.

replaceMissing(Object, Object, Object) - Static method in class tech.v3.TMD

Replace the missing values from a column or set of columns.

replaceMissing(Object, Object) - Static method in class tech.v3.TMD

Replace missing values.

reservoirDataset(long) - Static method in class tech.v3.dataset.Reductions

Return a reducer that produces a probabilistically sampled dataset of at most nRows len.

reservoirStats(Object, long, Object) - Static method in class tech.v3.dataset.Reductions

Return a reducer which will probabilistically sample the source column producing at most nRows and then call descriptiveStatistics on it with statName.

reverseRows(Object) - Static method in class tech.v3.TMD

Reverse the rows of the dataset

Rolling - Class in tech.v3.dataset

Fixed and variable length rolling windows.

rolling(Object, Map, Map) - Static method in class tech.v3.dataset.Rolling

Fixed or variable rolling window reductions.

rowCount(Object) - Static method in class tech.v3.dataset.Reductions

Returns a rowCount reducer that returns the number of source rows aggregated.

rowCount(Object) - Static method in class tech.v3.TMD

Return the number of rows.

rowMap(Object, IFn) - Static method in class tech.v3.TMD

Map a function across the rows of the dataset with each row in map form.

rowMap(Object, IFn, Object) - Static method in class tech.v3.TMD

Map a function across the rows of the dataset with each row in map form.

rowMapcat(Object, IFn, Object) - Static method in class tech.v3.TMD

Map a function across the rows of the dataset with each row in map form.

rows(Object) - Static method in class tech.v3.TMD

Return the rows of the dataset in a flyweight map format.

rowvecs(Object, boolean) - Static method in class tech.v3.TMD

Return the rows of the dataset where each row is just a flat Buffer of data.

rowvecs(Object) - Static method in class tech.v3.TMD

Return the rows of the dataset where each row is just a flat Buffer of data.

S

sample(Object) - Static method in class tech.v3.TMD

Return a random sampling of 5 rows without replacement of the data

sample(Object, long) - Static method in class tech.v3.TMD

Return a random sampling of N rows without replacement of the data

sample(Object, long, Map) - Static method in class tech.v3.TMD

Return a random sampling of N rows of the data.

select(Object, Object, Object) - Static method in class tech.v3.TMD

Select a sub-rect of the dataset.

selectColumns(Object, Object) - Static method in class tech.v3.TMD

Select columns by name.

selectRows(Object, Object) - Static method in class tech.v3.TMD

Select rows by index.

setCardinality(Object) - Static method in class tech.v3.dataset.Reductions

Returns a distinct reducer returns the number of distinct elements.

setCardinalityUint32(Object) - Static method in class tech.v3.dataset.Reductions

Returns a distinct reducer that expects unsigned integer values and returns the number of distinct elements.

setInferenceTarget(Object, Object) - Static method in class tech.v3.dataset.Modelling

Set a column in the dataset as the inference target.

shuffle(Object) - Static method in class tech.v3.TMD

Randomly shuffle the dataset rows.

shuffle(Object, Map) - Static method in class tech.v3.TMD

Randomly shuffle the dataset rows.

sortBy(Object, IFn, Object, Object) - Static method in class tech.v3.TMD

Sort a dataset by first mapping sortFn over it and then sorting over the result.

sortBy(Object, IFn, Object) - Static method in class tech.v3.TMD

Sort a dataset.

sortBy(Object, IFn) - Static method in class tech.v3.TMD

Sort a dataset.

sortByColumn(Object, Object, Object, Object) - Static method in class tech.v3.TMD

Sort a dataset by using the values from column cname.

sortByColumn(Object, Object, Object) - Static method in class tech.v3.TMD

Sort a dataset by a specific column.

sortByColumn(Object, Object) - Static method in class tech.v3.TMD

Sort a dataset by a specific column.

stddev(Object) - Static method in class tech.v3.dataset.Rolling

stddev reducer

streamToDataset(Object, Object) - Static method in class tech.v3.libs.Arrow

Load an apache arrow streaming file returning a single dataset.

streamToDatasetSeq(Object, Object) - Static method in class tech.v3.libs.Arrow

Load an apache arrow streaming file returning a sequence of datasets, one for each record batch.

sum(Object) - Static method in class tech.v3.dataset.Reductions

Returns a summation reducer that sums an individual source column.

sum(Object) - Static method in class tech.v3.dataset.Rolling

sum reducer

T

tail(Object) - Static method in class tech.v3.TMD

Return the last 5 rows of the dataset

tail(Object, long) - Static method in class tech.v3.TMD

Return the last N rows of the dataset

tech.v3 - package tech.v3

tech.v3.dataset - package tech.v3.dataset

tech.v3.libs - package tech.v3.libs

tensorToDataset(Object) - Static method in class tech.v3.TMD

Convert a tensor to a dataset such that the columns of the tensor become the columns of the dataset named after their index.

TMD - Class in tech.v3

tech.ml.dataset is a high performance library for processing columnar data similar to pandas or R’ data table.

toNeanderthal(Object, Keyword, Keyword) - Static method in class tech.v3.TMD

Convert a dataset to a neanderthal 2D matrix such that the columns of the dataset become the columns of the matrix.

toNeanderthal(Object) - Static method in class tech.v3.TMD

Convert a dataset to a neanderthal 2D matrix such that the columns of the dataset become the columns of the matrix.

toTensor(Object, Keyword) - Static method in class tech.v3.TMD

Convert a dataset to a jvm-heap based 2D tensor such that the columns of the dataset become the columns of the tensor.

toTensor(Object) - Static method in class tech.v3.TMD

Convert a dataset to a jvm-heap based 2D double (float64) tensor.

trainTestSplit(Object, Object) - Static method in class tech.v3.dataset.Modelling

Split the dataset returning a map of {:train-ds :test-ds}.

trainTestSplit(Object) - Static method in class tech.v3.dataset.Modelling

Randomize then split dataset using 70% of the data for training and the rest for testing.

transformCategorical(Object, Object) - Static method in class tech.v3.dataset.Modelling

Apply an object->integer transformation with data obtained from fitCategorical.

transformMinMax(Object, Object) - Static method in class tech.v3.dataset.Modelling

Transform a dataset using a previously fit minimax transformation.

transformOneHot(Object, Object) - Static method in class tech.v3.dataset.Modelling

Transform a dataset using a fitted one-hot mapping.

transformPCA(Object, Object) - Static method in class tech.v3.dataset.Modelling

Transform a dataset by the PCA fit data.

transformStdScale(Object, Object) - Static method in class tech.v3.dataset.Modelling

Transform dataset to mean of zero and a standard deviation of 1.

U

uniqueBy(Object, IFn) - Static method in class tech.v3.TMD

Create a dataset with no duplicates by taking first of duplicate values.

uniqueByColumn(Object, Object) - Static method in class tech.v3.TMD

Make a dataset unique using a particular column as the uniqueness criteria and taking the first value.

V

variableWindow(Object, double) - Static method in class tech.v3.dataset.Rolling

Create a variable window specification with a double windowsize for a particular column.

variableWindow(Object, double, Object) - Static method in class tech.v3.dataset.Rolling

Create a variable window specification with a double windowsize for a particular column and a compFn which must take two values and return a double.

variableWindow(Object, double, Keyword) - Static method in class tech.v3.dataset.Rolling

Create a datetime-specific variable window specification with a double windowsize for a particular column.

variance(Object) - Static method in class tech.v3.dataset.Rolling

variance reducer

W

writeDataset(Object, String, Object) - Static method in class tech.v3.TMD

Write a dataset to disc as csv, tsv, csv.gz, tsv.gz, json, json.gz or nippy.

writeDataset(Object, String) - Static method in class tech.v3.TMD

Write a dataset to disc as csv, tsv, csv.gz, tsv.gz or nippy.

A C D F G H I J K L M N P R S T U V W