v0.2.1
NEW
- Ten new statistical metrics (fbscore, r2score, matthews correlation coeff etc.).
- Two categorical encoding schemes (lexicographical and frequency).
- Time/Date encoding.
- Multiple hyper-parameter inputs now supported in FRESH.
- Two new significant features selection options (k-best & percentile).
MODIFICATIONS - Input structure modification to
.ml.fresh.createfeatures
full explanation at
(code.kx.com/ml/toolkit/fresh). - Input structure modification to
.ml.fresh.significantfeatures
to account for
additional significant feature selection methods. - Removal of
.ml.util
namespace, compression to.ml
. This tidys implementations and
removes ambiguity arising relating to if functions were true utils.
NOTE: functions below here may have previously been in.ml.util
namespace. - Underlying file structure change to tidies code locations within toolkit
statistical functions -> util/metrics.q,
true utils -> util/util.q,
preprocessing functions -> util/preproc.q. .ml.onehot
no longer supports lists, input expected as tables. Encoding can be set to
operate on a column by column basis..ml.comb
returns combinations in ascending order, previous implementation
had non-obvious return pattern..ml.filltab
has modified expected dictionary input, previous behaviour was
`linear`mean`median!`x`x1`x2
, this has been changed to a more 'q like'
mapping of columns to desired behaviours`x`x1`x2!`linear`mean`median
..ml.filltab
no longer default forward+backward fills on entry of ()!(), entry of
empty dictionary now returns original table. Defaulted forward+backward fill is
achieved through entry of::
in place of dict..ml.dropconstant
now supports removal of constant keys of a dictionary
FIXES.ml.infreplace
only worked correctly under the condition that both positive and
negative infinities existed within the vector. Function now operates if positive,
negative or no infinities are present in the vector.
REMOVED.ml.util.traintestsplitseed
, behaviour can be set viaq)\S x
prior
to application of.ml.traintestsplit.