This section describes each of the services compared in the throwdown and the algorithms/models used.
Decision trees.
JSON PML: schemas for models
model-schema.json A generic ML model, containing fields shared by most models despite of their concrete type. It uses:
sample-schema.json The schema for dataset sampling specificationsfield-collection-schema.json Auxiliary schema describing a collection of field (or "properties") descriptorsgeneric-field-schema.json Properties shared by all fields, regardless of their type.field-schema.json The union schema of all field descriptor types, with their specific properties.tree-model-schema.json A specialization of the model schema to decision tree models. It uses:node-schema The schema for the nodes in a decision tree| # import BigML class | |
| from bigml.api import BigML | |
| # import local Model class | |
| from bigml.model import Model | |
| # Instantiate the API with your credentials. You can avoid this if you set up your username and API key in your environment | |
| api = BigML('yourusername', '3ff25044b4f4582903d90000a5fab240442e734c') | |
| # Get the model. Assuming that you already created in BigML |
| from bigml.api import BigML | |
| from bigml.model import Model | |
| api = BigML() | |
| def support_vs_confidence(model_id): | |
| model = api.get_model(model_id) | |
| local_model = Model(model) | |
| leaves = local_model.get_leaves() | |
| outputs = unique([leaf['output'] for leaf in leaves]) | |
| colors = linspace(0, 1, len(outputs)) |
| <!DOCTYPE html> | |
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| body { | |
| font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; | |
| margin: auto; | |
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| width: 960px; | |
| background: #fff; |
| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <style> | |
| body { | |
| font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; | |
| margin: auto; | |
| position: relative; | |
| width: 960px; | |
| background: #fff; |
| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <style> | |
| body { | |
| font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; | |
| margin: auto; | |
| position: relative; | |
| width: 960px; | |
| background: #fff; |
| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <style> | |
| body { | |
| font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; | |
| margin: auto; | |
| position: relative; | |
| width: 960px; | |
| background: #fff; |
| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <style> | |
| body { | |
| font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; | |
| margin: auto; | |
| position: relative; | |
| width: 960px; | |
| background: #fff; |
| <!DOCTYPE html> | |
| <meta charset="utf-8"> | |
| <style> | |
| body { | |
| font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; | |
| margin: auto; | |
| position: relative; | |
| width: 960px; | |
| background: #fff; |