mmerce
/ evaluation.json
Created
September 29, 2015 19:56
Cross-validation result example for classification
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| {"model": {"average_phi": 0.9202600000000001, "average_f_measure_standard_deviation": 0.013335000000000041, "average_recall_standard_deviation": 0.013334999999999986, "average_recall": 0.946665, "average_precision_standard_deviation": 0.013355000000000006, "per_class_statistics": [{"recall_standard_deviation": 0.0, "accuracy_standard_deviation": 0.0, "phi_coefficient_standard_deviation": 0.0, "average_phi_coefficient": 1.0, "f_measure_standard_deviation": 0.0, "class_name": "Iris-setosa", "precision_standard_deviation": 0.0, "average_f_measure": 1.0, "average_accuracy": 1.0, "occurrences": 2, "average_recall": 1.0, "present_in_test_data": true, "average_precision": 1.0}, {"recall_standard_deviation": 0.019999999999999962, "accuracy_standard_deviation": 0.013333333333333308, "phi_coefficient_standard_deviation": 0.029716081940637296, "average_phi_coefficient": 0.8815770975722392, "f_measure_standard_deviation": 0.019607843137254832, "class_name": "Iris-versicolor", "precision_standard_deviation": 0.01923076923 |
mmerce
/ reify_dataset_with_fields.py
Created
September 4, 2015 18:19
BigMLer - reify dataset with fields code
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| """Python code to reify dataset/55e5e08e1fa89c24f8005e49 | |
| """ | |
| from bigml.api import BigML | |
| api = BigML() | |
| source1 = api.create_source("tiny_kdd.csv") | |
| api.ok(source1) |
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| bigmler reify --id dataset/55e5e08e1fa89c24f8005e49 \ | |
| --add-fields \ | |
| --output-dir my_dataset_with_fields |
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| """Python code to reify dataset/55e5e08e1fa89c24f8005e49 | |
| """ | |
| from bigml.api import BigML | |
| api = BigML() | |
| source1 = api.create_source("tiny_kdd.csv") | |
| api.ok(source1) |
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| bigmler reify --id dataset/55e5e08e1fa89c24f8005e49 \ | |
| --output-dir my_dataset |
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| """Python code to reify evaluation/55e9cb221fa89c24f80070df | |
| """ | |
| from bigml.api import BigML | |
| api = BigML() | |
| source1 = api.create_source("iris.csv") | |
| api.ok(source1) |
mmerce
/ reify_evaluation_output.txt
Created
September 4, 2015 18:04
BigMLer - reify evaluation output
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| Starting reification for evaluation/55e9cb221fa89c24f80070df | |
| [2015-09-04 18:50:06] Analyzing evaluation/55e9cb221fa89c24f80070df. | |
| [2015-09-04 18:50:08] New origin found for evaluation/55e9cb221fa89c24f80070df: model/55e9cb1e1fa89c24f80070dc | |
| [2015-09-04 18:50:08] Analyzing model/55e9cb1e1fa89c24f80070dc. | |
| [2015-09-04 18:50:08] New origin found for model/55e9cb1e1fa89c24f80070dc: dataset/55e9cb191fa89c24f80070d9 | |
| [2015-09-04 18:50:08] Analyzing dataset/55e9cb191fa89c24f80070d9. | |
| [2015-09-04 18:50:09] New origin found for dataset/55e9cb191fa89c24f80070d9: dataset/55e9cb161fa89c24f80070d6 | |
| [2015-09-04 18:50:09] Analyzing dataset/55e9cb161fa89c24f80070d6. | |
| [2015-09-04 18:50:09] New origin found for dataset/55e9cb161fa89c24f80070d6: source/55e9cb131fa89c24f80070d0 |
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| bigmler reify --id evaluation/55e744b70d052e234a00171f \ | |
| --output-dir my_evaluation |
mmerce
/ BigMLer_anomaly_1_c.sh
Created
June 15, 2015 18:49
Creating an anomaly detector reading data from stdin with BigMLer
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| cat vowel.csv | bigmler anomaly --train |
mmerce
/ BigMLer_anomaly_1_b.sh
Created
June 15, 2015 18:47
Creating an anomaly from a remote dataset with BigMLer
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| bigmler anomaly --train http://wherever.com/vowel.csv |