ir models. A typical function will take a set of "prediction" and
+"observation" values to calculate the desired metric, unless noted
otherwise.
+Grouping is supported by all of these functions (except confusion matrix).
+
+@anchor list
+@par Prediction Met
ir models. A typical function will take a set of "prediction" and
+"observation" values to calculate the desired metric, unless noted
otherwise.
+Grouping is supported by all of these functions (except confusion matrix).
+
+@anchor list
+@par Prediction Met
he License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# Prediction Metrics
+# This m
Github user iyerr3 commented on the pull request:
https://github.com/apache/incubator-madlib/pull/42
Along with casting the columns to int in binary classification, we also
need to change docs/online-help/tests to reflect that boolean columns allowed
for observation columns.
---
he License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# Prediction Metrics
+# This m
he License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# Prediction Metrics
+# This m
Github user iyerr3 commented on the pull request:
https://github.com/apache/incubator-madlib/pull/42#issuecomment-23823
I have made some changes and added validation and online help functions (in
my [private fork
Github user iyerr3 commented on the pull request:
https://github.com/apache/incubator-madlib/pull/42#issuecomment-218301178
General comments:
- The distance functions (mean_*_error) all have the same structure except
the distance metric. I suggest refactoring the table creation
Github user decibel commented on the pull request:
https://github.com/apache/incubator-madlib/pull/41#issuecomment-216655743
I suggest starting with documentation and hold off a bit on the code.
There might be some even better ways to do things that what I initially
thought
Github user orhankislal closed the pull request at:
https://github.com/apache/incubator-madlib/pull/41
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Github user orhankislal commented on the pull request:
https://github.com/apache/incubator-madlib/pull/41#issuecomment-216651893
Thanks for your comments decibel. I'll close this pull request, review your
comments, update the code and documentation accordingly and create a new pull
Github user decibel commented on a diff in the pull request:
https://github.com/apache/incubator-madlib/pull/41#discussion_r61940732
--- Diff: src/ports/postgres/modules/pred_metrics/pred_metrics.py_in ---
@@ -0,0 +1,391 @@
+# coding=utf-8
+#
+# Licensed to the Apache
Github user decibel commented on a diff in the pull request:
https://github.com/apache/incubator-madlib/pull/41#discussion_r61935728
--- Diff: src/ports/postgres/modules/pred_metrics/pred_metrics.py_in ---
@@ -0,0 +1,391 @@
+# coding=utf-8
+#
+# Licensed to the Apache
GitHub user orhankislal opened a pull request:
https://github.com/apache/incubator-madlib/pull/41
Prediction Metrics: New module
JIRA: MADLIB-907
A collection of summary statistics to gauge model accuracy
based on predicted values vs. ground-truth values.
You can merge
Orhan,
I think this is a good addition to MADlib. Regarding your questions:
1) Seems like a good set of prediction metrics to start with. If other
members of the community would like to add more, they are welcome to create
a JIRA for those and work on them.
2) Suggest we do include grouping
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