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| Description |
| !1 Selection of the more accurate ANNs
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| | After ''n-runs'' of the training service, the most accurate ANNs are selected based on goodness of validation errors. User is asked to set 3 parameters in the payload (defaults provided):
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| | # __mechanism__ ''(default...threshold;
| | # __error__ ''(default nashSutcliffe)'': the error on which selecting the best ANNs.
| | !2 Available selection algorithms
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| | Following the list of available selection algorithm:
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| | # __percentile__: select the ANNs that outperform with respect to a |
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| !1 Selection of the more accurate ANNs
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| | After ''n-runs'' of the training service, the most accurate ANNs are selected based on godness of validation errors.¶ | | User is asked to set 3 parameters in the payload (defaults provided):
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| | # __mechanism__ ''(default...threshold;
| | # __error__ ''(default nashSutcliffe)'': the error on which selecting the best ANNs.
| | ¶ | | !2 Available selection algorithms
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| | Following the list of available selection algorithm:
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| | # __percentile__: select the best ANNs depending on a fixed | |
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| Description |
| !1 Selection of the more accurate ANNs
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| | After ''n-runs'' of the training service, the most accura...error;
| | # __number__: select the best ANNs based on a fixed threshold for the specified error.
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| | ¶ | | [{ DirectedAcyclicGraph title='Select service'¶ | | ¶ | | (¶ | | (JSON payload[:color:#009900][:background:#DDFFDD])¶ | | (test_ann/trained.files[database/collection][:color:#777777][:background:#DDDDDD])¶ | | (m/select/1.0[csip service][:depend:JSON payload][:depend:test_ann/trained.files][:color:red])¶ | | (test_ann/select[database/collection for storing best ANNs IDs][:depend:m/select/1.0][:color:#777777][:background:#DDDDDD])¶ | | )¶ | | }]¶ | | ¶ | | %%tabbedSection
| | %%tab-Request
| | {{{
| | {
| | "metainfo": {},
| | "parameter": [...;: "selected anns",
| | "value": 15
| | }
| | ]
| | }
| | }}}
| | %%
| | %% |
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| !1 Selection of the more accurate ANNs
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| | After ''n-runs'' of the training service, the most accura...error;
| | # __number__: select the best ANNs based on a fixed threshold for the specified error.
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| | %%tabbedSection
| | %%tab-Request
| | {{{
| | {
| | "metainfo": {},
| | "parameter": [...;: "selected anns",
| | "value": 15
| | }
| | ]
| | }
| | }}}
| | %%
| | %% | |
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| Description |
| !1 Selection of the more accurate ANNs¶ | | ¶ | | After ''n-runs'' of the training service, the most accurate ANNs are selected based on godness of validation errors.¶ | | User is asked to set 3 parameters in the payload (defaults provided):¶ | | ¶ | | # __mechanism__ ''(default percentile)'': the selection algorithm;¶ | | # __threshold__ ''(default 95)'': the threshold;¶ | | # __error__ ''(default nashSutcliffe)'': the error on which selecting the best ANNs.¶ | | ¶ | | !2 Available selection algorithms¶ | | ¶ | | Following the list of available selection algorithm:¶ | | ¶ | | # __percentile__: select the best ANNs depending on a fixed threshold for a percentile after analizing the distribution of the specified error;¶ | | # __number__: select the best ANNs based on a fixed threshold for the specified error.
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| | %%tabbedSection
| | %%tab-Request
| | {{{
| | {
| | "metainfo": {},
| | "parameter"...;: "selected anns",
| | "value": 15
| | }
| | ]
| | }
| | }}}
| | %%
| | %% |
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| This service selects a neural network.¶ | | ¶ | | !3 Selection
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| | %%tabbedSection
| | %%tab-Request
| | {{{
| | {
| | "metainfo": {},
| | "parameter"...;: "selected anns",
| | "value": 15
| | }
| | ]
| | }
| | }}}
| | %%
| | %% | |
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| Description |
| This service selects a neural network.¶ | | ¶ | | !3 Selection¶ | | ¶ | | %%tabbedSection¶ | | %%tab-Request¶ | | {{{¶ | | {¶ | | "metainfo": {},¶ | | "parameter": [¶ | | {¶ | | "name": "annName",¶ | | "value": "test_ann"¶ | | },¶ | | {¶ | | "name": "mechanism",¶ | | "value": "percentile"¶ | | },¶ | | {¶ | | "name": "threshold",¶ | | "value": 95¶ | | },¶ | | {¶ | | "name": "error",¶ | | "value": "nashSutcliffe"¶ | | }¶ | | ]¶ | | }¶ | | }}}¶ | | %%¶ | | %%tab-Response¶ | | {{{¶ | | {¶ | | "metainfo": {¶ | | "status": "Finished",¶ | | "suid": "d415ae19-f5d1-11e7-9386-8b11ee17256d",¶ | | "cloud_node": "10.1.33.2",¶ | | "request_ip": "129.82.23.199",¶ | | "service_url": "http://csip.engr.colostate.edu:8088/csip-ann/m/select/1.0",¶ | | "csip.version": "$version: 2.2.4 3c276d66bde6 2017-12-15 od, built at 2018-01-09 23:43 by jenkins$",¶ | | "tstamp": "2018-01-09 23:45:21",¶ | | "cpu_time": 834,¶ | | "expiration_date": "2018-01-09 23:45:52"¶ | | },¶ | | "parameter": [¶ | | {¶ | | "name": "annName",¶ | | "value": "test_ann"¶ | | },¶ | | {¶ | | "name": "mechanism",¶ | | "value": "percentile"¶ | | },¶ | | {¶ | | "name": "threshold",¶ | | "value": 95¶ | | },¶ | | {¶ | | "name": "error",¶ | | "value": "nashSutcliffe"¶ | | }¶ | | ],¶ | | "result": [¶ | | {¶ | | "name": "status",¶ | | "value": "ok"¶ | | },¶ | | {¶ | | "name": "error",¶ | | "value": "nashSutcliffe"¶ | | },¶ | | {¶ | | "name": "error treshold",¶ | | "value": 0.8259409682325399¶ | | },¶ | | {¶ | | "name": "selected anns",¶ | | "value": 15¶ | | }¶ | | ]¶ | | }¶ | | }}}¶ | | %%¶ | | %% |
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| This service selects a neural network. | |
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| Service Name |
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| Path |
m/select/1.0 |
m/train/1.0 |
| Description |
| This service selects a neural network. | |
| This service trains a neural network after splitting the data set into training and validation | |
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Submit
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1 |
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| Submitted at |
Jan 08 2018 11:30 |
Jan 06 2018 10:47 |
| Submitted by |
odavid |
sidereus |
|
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