Trait opencv::ml::TrainDataTrait

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pub trait TrainDataTrait: TrainDataTraitConst {
    // Required method
    fn as_raw_mut_TrainData(&mut self) -> *mut c_void;

    // Provided methods
    fn set_train_test_split(&mut self, count: i32, shuffle: bool) -> Result<()> { ... }
    fn set_train_test_split_def(&mut self, count: i32) -> Result<()> { ... }
    fn set_train_test_split_ratio(
        &mut self,
        ratio: f64,
        shuffle: bool
    ) -> Result<()> { ... }
    fn set_train_test_split_ratio_def(&mut self, ratio: f64) -> Result<()> { ... }
    fn shuffle_train_test(&mut self) -> Result<()> { ... }
}

Expand description

Mutable methods for crate::ml::TrainData

Required Methods§

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fn as_raw_mut_TrainData(&mut self) -> *mut c_void

Provided Methods§

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fn set_train_test_split(&mut self, count: i32, shuffle: bool) -> Result<()>

Splits the training data into the training and test parts

§See also

TrainData::setTrainTestSplitRatio

§C++ default parameters

shuffle: true

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fn set_train_test_split_def(&mut self, count: i32) -> Result<()>

Splits the training data into the training and test parts

§See also

TrainData::setTrainTestSplitRatio

§Note

This alternative version of TrainDataTrait::set_train_test_split function uses the following default values for its arguments:

shuffle: true

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fn set_train_test_split_ratio( &mut self, ratio: f64, shuffle: bool ) -> Result<()>

Splits the training data into the training and test parts

The function selects a subset of specified relative size and then returns it as the training set. If the function is not called, all the data is used for training. Please, note that for each of TrainData::getTrain* there is corresponding TrainData::getTest*, so that the test subset can be retrieved and processed as well.

§See also

TrainData::setTrainTestSplit

§C++ default parameters

shuffle: true

source

fn set_train_test_split_ratio_def(&mut self, ratio: f64) -> Result<()>

Splits the training data into the training and test parts

The function selects a subset of specified relative size and then returns it as the training set. If the function is not called, all the data is used for training. Please, note that for each of TrainData::getTrain* there is corresponding TrainData::getTest*, so that the test subset can be retrieved and processed as well.