Trait TrainDataTraitConst

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pub trait TrainDataTraitConst {
Show 36 methods    // Required method
    fn as_raw_TrainData(&self) -> *const c_void;

    // Provided methods
    fn get_layout(&self) -> Result<i32> { ... }
    fn get_n_train_samples(&self) -> Result<i32> { ... }
    fn get_n_test_samples(&self) -> Result<i32> { ... }
    fn get_n_samples(&self) -> Result<i32> { ... }
    fn get_n_vars(&self) -> Result<i32> { ... }
    fn get_n_all_vars(&self) -> Result<i32> { ... }
    fn get_sample(
        &self,
        var_idx: &impl ToInputArray,
        sidx: i32,
        buf: &mut f32,
    ) -> Result<()> { ... }
    fn get_samples(&self) -> Result<Mat> { ... }
    fn get_missing(&self) -> Result<Mat> { ... }
    fn get_train_samples(
        &self,
        layout: i32,
        compress_samples: bool,
        compress_vars: bool,
    ) -> Result<Mat> { ... }
    fn get_train_samples_def(&self) -> Result<Mat> { ... }
    fn get_train_responses(&self) -> Result<Mat> { ... }
    fn get_train_norm_cat_responses(&self) -> Result<Mat> { ... }
    fn get_test_responses(&self) -> Result<Mat> { ... }
    fn get_test_norm_cat_responses(&self) -> Result<Mat> { ... }
    fn get_responses(&self) -> Result<Mat> { ... }
    fn get_norm_cat_responses(&self) -> Result<Mat> { ... }
    fn get_sample_weights(&self) -> Result<Mat> { ... }
    fn get_train_sample_weights(&self) -> Result<Mat> { ... }
    fn get_test_sample_weights(&self) -> Result<Mat> { ... }
    fn get_var_idx(&self) -> Result<Mat> { ... }
    fn get_var_type(&self) -> Result<Mat> { ... }
    fn get_var_symbol_flags(&self) -> Result<Mat> { ... }
    fn get_response_type(&self) -> Result<i32> { ... }
    fn get_train_sample_idx(&self) -> Result<Mat> { ... }
    fn get_test_sample_idx(&self) -> Result<Mat> { ... }
    fn get_values(
        &self,
        vi: i32,
        sidx: &impl ToInputArray,
        values: &mut f32,
    ) -> Result<()> { ... }
    fn get_norm_cat_values(
        &self,
        vi: i32,
        sidx: &impl ToInputArray,
        values: &mut i32,
    ) -> Result<()> { ... }
    fn get_default_subst_values(&self) -> Result<Mat> { ... }
    fn get_cat_count(&self, vi: i32) -> Result<i32> { ... }
    fn get_class_labels(&self) -> Result<Mat> { ... }
    fn get_cat_ofs(&self) -> Result<Mat> { ... }
    fn get_cat_map(&self) -> Result<Mat> { ... }
    fn get_test_samples(&self) -> Result<Mat> { ... }
    fn get_names(&self, names: &mut Vector<String>) -> Result<()> { ... }
}

Expand description

Constant methods for crate::ml::TrainData

Required Methods§

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fn as_raw_TrainData(&self) -> *const c_void

Provided Methods§

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fn get_sample( &self, var_idx: &impl ToInputArray, sidx: i32, buf: &mut f32, ) -> Result<()>

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fn get_samples(&self) -> Result<Mat>

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fn get_missing(&self) -> Result<Mat>

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fn get_train_samples( &self, layout: i32, compress_samples: bool, compress_vars: bool, ) -> Result<Mat>

Returns matrix of train samples

§Parameters

layout: The requested layout. If it’s different from the initial one, the matrix is transposed. See ml::SampleTypes.
compressSamples: if true, the function returns only the training samples (specified by sampleIdx)
compressVars: if true, the function returns the shorter training samples, containing only the active variables.

In current implementation the function tries to avoid physical data copying and returns the matrix stored inside TrainData (unless the transposition or compression is needed).

§C++ default parameters

layout: ROW_SAMPLE
compress_samples: true
compress_vars: true

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fn get_train_samples_def(&self) -> Result<Mat>

Returns matrix of train samples

§Parameters

layout: The requested layout. If it’s different from the initial one, the matrix is transposed. See ml::SampleTypes.
compressSamples: if true, the function returns only the training samples (specified by sampleIdx)
compressVars: if true, the function returns the shorter training samples, containing only the active variables.

In current implementation the function tries to avoid physical data copying and returns the matrix stored inside TrainData (unless the transposition or compression is needed).

§Note

This alternative version of TrainDataTraitConst::get_train_samples function uses the following default values for its arguments:

layout: ROW_SAMPLE
compress_samples: true
compress_vars: true

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fn get_train_responses(&self) -> Result<Mat>

Returns the vector of responses

The function returns ordered or the original categorical responses. Usually it’s used in regression algorithms.

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fn get_train_norm_cat_responses(&self) -> Result<Mat>

Returns the vector of normalized categorical responses

The function returns vector of responses. Each response is integer from 0 to <number of classes>-1. The actual label value can be retrieved then from the class label vector, see TrainData::getClassLabels.

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