Frank McQuillan created MADLIB-1452:
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Summary: Add top n to evalute()
Key: MADLIB-1452
URL: https://issues.apache.org/jira/browse/MADLIB-1452
Project: Apache MADlib
Issue Type: Improvement
Components: Deep Learning
Reporter: Frank McQuillan
Fix For: v1.18.0
Applies to
https://madlib.apache.org/docs/latest/group__grp__keras.html#keras_evaluate
&
https://madlib.apache.org/docs/latest/group__grp__keras__run__model__selection.html#keras_evaluate
Add a new parameter to the evaluate interface:
{code}
madlib_keras_evaluate(
model_table,
test_table,
output_table,
use_gpus,
mst_key,
top_n -- new parameter
)
{code}
{code}
top_n (optional)
INTEGER[], default {1}. Array of top values to compute accuracy percentages
using the metric from the training set. E.g., {1, 5, 10} means compute the
top-1, top-5 and top-10 classification accuracies.
{code}
Add 2 new columns to the right side of the output table:
{code}
output_table
TEXT. Name of table that validation output will be written to. Table contains:
loss Loss value on evaluation dataset.
metric Metric value on evaluation dataset, where
'metrics_type' below identifies the type of metric.
metrics_type Type of metric used that was used in the
training step.
top_n_accuracy Array of percentage accuracies as per metric _type
top_n Array defining the top n values used.
{code}
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