aficionado

{
  "name": "Incremental anomalies",
  "kind": "script",
  "description": "Adds a new dataset to a collection and computes a set of anomalies for the new, extended data",
  "source_code": "script.whizzml",
  "imports":[
    ],
  "inputs":[
    {
      "name": "url",

aficionado

{
    "name": "Merge two datasets",
    "description": "Merges two different datasets",
    "source_code": "script.whizzml",
    "inputs": [
        {
            "name": "dataset-1",
            "type": "dataset-id",
            "description": "First dataset"
        },

aficionado

{
  "name": "Tree optimization",
  "description": "Script for tree optimization using SMACdown",
  "kind": "script",
  "source_code": "script.whizzml",
  "inputs":[
    {
      "name": "dataset-id",
      "type": "dataset-id",
      "description": "Dataset for which we are seeking an optimal tree"

aficionado

#!/usr/bin/env python
"""A WhizzML simple example

"""

from bigml.api import BigML

API = BigML()

LIBRARY = API.create_library("(define (addition a b) (+ a b))")

aficionado

;; This is a vanilla implementation of gradient boosting.  The main
;; function is at the bottom of the script, where it explains the
;; algorithm in some detail.

;; A constant added to the generated field names to let us know that
;; we generated them
(define boost-id "__bmlboost")

;; The names of the fields contain ground truth - if there are k
;; classes, this is k coluns, one for each class.  If the true class

aficionado

{
    "name": "Model or ensemble",
    "description": "Select the best option for modeling a source: a model or an ensemble?",
    "parameters": [
        {
            "name": "input-source-id",
            "type": "source-id",
            "description": "Source for training/test the model and ensemble"
        }
    ],

aficionado

{
  "name": "One-Click Dataset",
  "description": "Create a new dataset from a source with a click",
  "outputs": [
    {"name": "dataset-id", "type": "dataset-id", "description": "The new dataset"},
    {"name": "rows", "type": "number", "description": "The number of rows of the new dataset"}
  ],
  "parameters": [
    {"name": "source-id", "type": "source-id", "default": "", "description": "Source from which to create a new dataset"},
    {"name": "source-name", "type": "string", "default": "", "description": "Name for the new dataset"}

aficionado

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Moves a resource to a project

"""

##############################################################################
# Copyright (c) 2015 BigML, Inc
#
# Permission is hereby granted, free of charge, to any person obtaining

aficionado

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Uses multiple confidence thresholds to evaluate a model.

"""

##############################################################################
# Copyright (c) 2015 BigML, Inc
#
# Permission is hereby granted, free of charge, to any person obtaining

aficionado

from pymongo.son_manipulator import SONManipulator

class KeyTransform(SONManipulator):
    """Transforms keys going to database and restores them coming out.

    This allows keys with dots in them to be used (but does break searching on
    them unless the find command also uses the transform.

    Example & test:
        # To allow `.` (dots) in keys