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Creates a link between each row and the N rows most similar to it. Broadly, the similarity between two rows is a weighted similarity of the individual columns. The step accepts all data types, i.e. texts, quantitative, categorical columns etc.

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Usage

The following example shows how the step can be used in a recipe.

Examples

  • Example 1
  • Signature
link_similar_rows(ds[["bio", "salary", "age", "department"]]) -> (links)

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Inputs & Outputs

The following are the inputs expected by the step and the outputs it produces. These are generally columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced by name e.g. "churn-clf").
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ds
dataset
required
A dataset containing the columns to be included in the calculation of pair-wise similarities. Note: a subset of columns can always be selected in a recipe using the ds[[“column1”, “column2”, …]] syntax. Or to exclude: ds[![“column1”, “column2”, …]].
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targets
column
required
A column containing for each row a list of row numbers identfying all other rows it is similar to.
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weights
column
required
A column containing for each row a list of weights identfying the “importance” of each link to other rows identified in the targets column (identifying how similar the rows are).

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Configuration

The following parameters can be used to configure the behaviour of the step by including them in a json object as the last “input” to the step, i.e. step(..., {"param": "value", ...}) -> (output).

Parameters

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n_similar_docs
integer
default:"10"
Number of similar docs.Values must be in the following range:
1 ≤ n_similar_docs < inf
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minhash
boolean
default:"false"
Whether to use minhash as a similarity measure.
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n_terms
integer
default:"15"
Number of terms to use.Values must be in the following range:
1 ≤ n_terms < inf
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min_term_freq
integer
default:"2"
Minimum term frequency. (For TFIDF).Values must be in the following range:
0 ≤ min_term_freq < inf
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min_doc_freq
integer
default:"2"
Minimum doc frequency. (For TFIDF).Values must be in the following range:
0 ≤ min_doc_freq < inf
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max_doc_perc
number
default:"0.9"
Maximum doc percentage. (For TFIDF).Values must be in the following range:
0 ≤ max_doc_perc ≤ 1
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min_should_match
integer
default:"2"
Minimum of terms that should match.Values must be in the following range:
0 ≤ min_should_match < inf
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separator
string
default:"[\\W0-9]{1,100}"
Regex to recognize as string separator.
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stopwords_langs
string
default:"ES,EN"
Languages to use for stopwords. supports ES, EN and both using commas “ES,EN”.Values must be one of the following:
  • ES
  • EN
  • ES,EN
  • EN,ES
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