TfidfVectorizer - text-col - default -#

Fitted on a problem type text-col (see find_suitable_problem), method transform matches output .

TfidfVectorizer()

index

0

skl_nop

1

onx_size

1285

onx_nnodes

8

onx_ninits

2

onx_doc_string

onx_ir_version

8

onx_domain

ai.onnx

onx_model_version

0

onx_producer_name

skl2onnx

onx_producer_version

1.11.1

onx_

14

onx_ai.onnx.ml

1

onx_com.microsoft

1

onx_op_Identity

1

onx_op_Reshape

1

onx_size_optim

1233

onx_nnodes_optim

7

onx_ninits_optim

2
%0 X X str((0,)) Reshape Reshape (Reshape) X->Reshape variable variable float((0, 18)) shape_tensor shape_tensor int64((1,)) [-1] shape_tensor->Reshape idfcst idfcst float32((18,)) [3.442347 3.442347 3.442347 3.036882 3.442347 3.44... Mul Mul (Mul) idfcst->Mul flattened flattened StringNormalizer StringNormalizer (StringNormalizer) case_change_action=b'LOWER' is_case_sensitive=0 flattened->StringNormalizer Reshape->flattened normalized normalized Tokenizer Tokenizer (Tokenizer) mark=0 mincharnum=1 pad_value=b'#' tokenexp=b'[a-zA-Z0-9_]+' normalized->Tokenizer StringNormalizer->normalized tokenized tokenized Flatten Flatten (Flatten) tokenized->Flatten Tokenizer->tokenized flattened1 flattened1 TfIdfVectorizer TfIdfVectorizer (TfIdfVectorizer) max_gram_length=1 max_skip_count=0 min_gram_length=1 mode=b'TF' ngram_counts=[0] ngram_indexes=[ 0  1  2  3  4  ... pool_strings=[b'dix' b'eighteen... weights=[1. 1. 1. 1. 1. 1. 1. 1... flattened1->TfIdfVectorizer Flatten->flattened1 output output output->Mul TfIdfVectorizer->output tfidftr_output tfidftr_output Normalizer Normalizer (Normalizer) norm=b'L2' tfidftr_output->Normalizer Mul->tfidftr_output tfidftr_norm tfidftr_norm Identity Identity (Identity) tfidftr_norm->Identity Normalizer->tfidftr_norm Identity->variable

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