[
https://issues.apache.org/jira/browse/MAHOUT-1856?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15830810#comment-15830810
]
ASF GitHub Bot commented on MAHOUT-1856:
----------------------------------------
Github user dlyubimov commented on a diff in the pull request:
https://github.com/apache/mahout/pull/246#discussion_r96982250
--- Diff:
math-scala/src/main/scala/org/apache/mahout/math/algorithms/regression/Regressor.scala
---
@@ -0,0 +1,33 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the 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.
+ */
+
+package org.apache.mahout.math.algorithms.regression
+
+import org.apache.mahout.math.algorithms.Model
+import org.apache.mahout.math.drm.DrmLike
+
+/**
+ * Abstract of Regressors
+ */
+abstract class Regressor extends Model {
+
+ def fit[Int](drmY: DrmLike[Int], drmX: DrmLike[Int]): Unit
--- End diff --
i guess if this is abstract enough, we also need to be able admit
hyperparameters which are of course specific for every fitter. in R this is
trivial (any call can be made a bag of whatever named arguments), but in Scala
this may need a bit of a thought (if this abstraction needs to be that high).
otherwise, i guess most scala kits just create a concrete fit signature per
implementation.
if the Regressor trait is meant to be common to all possible regression
class algorithms, we either need a way to universally pass in the
hyperparameters, or just not have fit abstraction in the regressor trait at all
. (then what i guess :) )
> Create a framework for new Mahout Clustering, Classification, and
> Optimization Algorithms
> ------------------------------------------------------------------------------------------
>
> Key: MAHOUT-1856
> URL: https://issues.apache.org/jira/browse/MAHOUT-1856
> Project: Mahout
> Issue Type: New Feature
> Affects Versions: 0.12.1
> Reporter: Andrew Palumbo
> Assignee: Trevor Grant
> Priority: Critical
> Fix For: 0.13.0
>
>
> To ensure that Mahout does not become "A loose bag of algorithms", Create
> basic traits with funtions common to each class of algorithm.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
