jubaclient

jubaclient

Jubatus CLI client (unofficial)

Quick Start

# installation
npm install -g jubaclient

# startup jubaclassifier
jubaclassifier -f ./config.json -D

# classifier#train()
echo '[ [ [ "baz", [ [ [ "foo", "bar" ] ] ] ] ] ]' \
| jubaclient classifier train

Requires

• Node.js v6+

Installation

npm install -g jubaclient

Usage

jubaclient service method [-p port] [-h hostname] [-n name] [-t timeoutSeconds]

jubaclient -i [service] [method] [-p port] [-h hostname] [-n name] [-t timeoutSeconds]

The jubaclient command requests JSON received from standard input with the specified method to the Jubatus server, and returns the response to the standard output.

The command line options are as follows:

• service: sevice name (classifier, nearest_neighbor, etc.)
• method: service method (get_status, train, get_k_center, etc.)
• -p port : port number (default 9199)
• -h hostname : hostname (default localhost)
• -n name : name of target cluster (default '')
• -t timeoutSeconds : timeout (default 0)
• -i : interactive mode

Examples

• #save(id)

  echo '[ "jubaclient_save_1" ]' | jubaclient classifier save 
  

• #get_status()

  echo '[]' | jubaclient classifier get_status | jq '.' 
  

• #get_config()

  echo '[]' | jubaclient classifier get_config | jq '.|fromjson' 
  

• classifier#train(data)

  jubaclient classifier train <<EOF | jq '.'
  [ [ [ "corge", [ [ [ "message", "<p>foo</p>" ] ] ] ] ] ]
  [ [ [ "corge", [ [ [ "message", "<p>bar</p>" ] ] ] ] ] ]
  [ [ [ "corge", [ [ [ "message", "<p>baz</p>" ] ] ] ] ] ]
  [ [ [ "grault", [ [ [ "message", "<p>qux</p>" ] ] ] ] ] ]
  [ [ [ "grault", [ [ [ "message", "<p>quux</p>" ] ] ] ] ] ]
  EOF
  

• classifier#classify(data)

  jubaclient classifier classify <<EOF | jq '.'
  [ [ [ [ [ "message", "<b>quuz</b>" ] ] ] ] ]
  EOF
  

Interactive mode

Demonstration

Tutorial

Classifier

See also http://jubat.us/en/tutorial/classifier.html

Demonstration

1. start jubaclassifier process.

   jubaclassifier -D --configpath gender.json 
   

2. train

   cat train.csv \
   | jq -RcM 'split(",")|[[[.[0],[[["hair",.[1]],["top",.[2]],["bottom",.[3]]],[["height",(.[4]|tonumber)]]]]]]' \
   | jubaclient classifier train
   

3. classify

   cat classify.csv \
   | jq -RcM 'split(",")|[[[[["hair",.[0]],["top",.[1]],["bottom",.[2]]],[["height",(.[3]|tonumber)]]]]]' \
   | jubaclient classifier classify \
   | jq '.[]|max_by(.[1])'
   

configure: gender.json

{
  "method": "AROW",
  "converter": {
    "num_filter_types": {}, "num_filter_rules": [],
    "string_filter_types": {}, "string_filter_rules": [],
    "num_types": {}, "num_rules": [],
    "string_types": {
      "unigram": { "method": "ngram", "char_num": "1" }
    },
    "string_rules": [
      { "key": "*", "type": "unigram", "sample_weight": "bin", "global_weight": "bin" }
    ]
  },
  "parameter": { "regularization_weight" : 1.0 }
}

training data: train.csv

male,short,sweater,jeans,1.70
female,long,shirt,skirt,1.56
male,short,jacket,chino,1.65
female,short,T shirt,jeans,1.72
male,long,T shirt,jeans,1.82
female,long,jacket,skirt,1.43

test data: classify.csv

short,T shirt,jeans,1.81
long,shirt,skirt,1.50