Struct TFIDFData 

pub struct TFIDFData<N = f32, K = String, E = DefaultTFIDFEngine>
where
    N: Num + Copy,
    E: TFIDFEngine<N>,
{
    pub documents: Vec<TFVector<N, K>>,
    pub token_dim_sample: IndexSet<String, RandomState>,
    pub idf: IDFVector<N>,
    /* private fields */
}

Data structure for deserializing TFIDFVectorizer. This struct does not contain references, so it can be serialized. Use the into_tf_idf_vectorizer method to convert to TFIDFVectorizer.

Fields

documents: Vec<TFVector<N, K>>

TF vectors for documents

token_dim_sample: IndexSet<String, RandomState>

Token dimension sample for TF vectors

idf: IDFVector<N>

IDF vector

Implementations

impl<N, K, E> TFIDFData<N, K, E>

where N: Num + Copy, E: TFIDFEngine<N>,

pub fn into_tf_idf_vectorizer( self, corpus_ref: Arc<Corpus>, ) -> TFIDFVectorizer<N, K, E>

Convert TFIDFData into TFIDFVectorizer. corpus_ref is a reference to the corpus.

Trait Implementations

impl<N, K: Debug, E> Debug for TFIDFData<N, K, E>

where N: Num + Copy + Debug, E: TFIDFEngine<N> + Debug,

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de, N, K, E> Deserialize<'de> for TFIDFData<N, K, E>

where N: Num + Copy + Deserialize<'de>, E: TFIDFEngine<N>, K: Deserialize<'de>,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<N, K, E> Serialize for TFIDFData<N, K, E>

where N: Num + Copy + Serialize, E: TFIDFEngine<N>, K: Serialize,

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.