Univariate feature ranking for classification using chi-square tests
ranks features (predictors) using chi-square tests.
The table idx
= fscchi2(Tbl
,ResponseVarName
)Tbl
contains predictor variables and a response variable,
and ResponseVarName
is the name of the response variable in
Tbl
. The function returns idx
, which contains
the indices of predictors ordered by predictor importance, meaning
idx(1)
is the index of the most important predictor. You can use
idx
to select important predictors for classification
problems.
specifies additional options using one or more name-value pair arguments in addition to
any of the input argument combinations in the previous syntaxes. For example, you can
specify prior probabilities and observation weights.idx
= fscchi2(___,Name,Value
)
If you specify the response variable and predictor variables by using the input argument
formula
, then the variable names in the formula must be both
variable names in Tbl
(Tbl.Properties.VariableNames
)
and valid MATLAB identifiers.
You can verify the variable names in Tbl
by using the isvarname
function. The following code returns logical 1
(true
) for each variable that has a valid variable name.
cellfun(@isvarname,Tbl.Properties.VariableNames)
Tbl
are not valid, then convert them by using the
matlab.lang.makeValidName
function.Tbl.Properties.VariableNames = matlab.lang.makeValidName(Tbl.Properties.VariableNames);