Merge branch 'master' into jupyter

salesforce · Mar 7, 2019 · 41bd221 · 41bd221
2 parents c84758f + 4da94f8
commit 41bd221
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Showing 2 changed files with 19 additions and 10 deletions.
diff --git a/core/src/main/scala/com/salesforce/op/stages/impl/feature/Transmogrifier.scala b/core/src/main/scala/com/salesforce/op/stages/impl/feature/Transmogrifier.scala
@@ -79,6 +79,11 @@ private[op] trait TransmogrifierDefaults {
   val MaxCategoricalCardinality = 30
   val CircularDateRepresentations: Seq[TimePeriod] = Seq(TimePeriod.HourOfDay, TimePeriod.DayOfWeek,
     TimePeriod.DayOfMonth, TimePeriod.DayOfYear)
+
+  val DefaultRegion: String = PhoneNumberParser.DefaultRegion
+  val AutoDetectLanguage: Boolean = TextTokenizer.AutoDetectLanguage
+  val MinTokenLength: Int = TextTokenizer.MinTokenLength
+  val ToLowercase: Boolean = TextTokenizer.ToLowercase
 }
 
 private[op] object TransmogrifierDefaults extends TransmogrifierDefaults
@@ -178,7 +183,7 @@ private[op] case object Transmogrifier {
             trackNulls = TrackNulls, trackInvalid = TrackInvalid, minInfoGain = MinInfoGain, label = label)
         case t if t =:= weakTypeOf[PhoneMap] =>
           val (f, other) = castAs[PhoneMap](g) // TODO make better default
-          f.vectorize(defaultRegion = PhoneNumberParser.DefaultRegion, others = other, trackNulls = TrackNulls)
+          f.vectorize(defaultRegion = DefaultRegion, others = other, trackNulls = TrackNulls)
         case t if t =:= weakTypeOf[PickListMap] =>
           val (f, other) = castAs[PickListMap](g)
           f.vectorize(topK = TopK, minSupport = MinSupport, cleanText = CleanText, cleanKeys = CleanKeys,
@@ -190,15 +195,15 @@ private[op] case object Transmogrifier {
         case t if t =:= weakTypeOf[TextAreaMap] =>
           val (f, other) = castAs[TextAreaMap](g)
           f.smartVectorize(maxCategoricalCardinality = MaxCategoricalCardinality,
-            numHashes = DefaultNumOfFeatures, autoDetectLanguage = TextTokenizer.AutoDetectLanguage,
-            minTokenLength = TextTokenizer.MinTokenLength, toLowercase = TextTokenizer.ToLowercase,
+            numHashes = DefaultNumOfFeatures, autoDetectLanguage = AutoDetectLanguage,
+            minTokenLength = MinTokenLength, toLowercase = ToLowercase,
             prependFeatureName = PrependFeatureName, cleanText = CleanText, cleanKeys = CleanKeys,
             others = other, trackNulls = TrackNulls)
         case t if t =:= weakTypeOf[TextMap] =>
           val (f, other) = castAs[TextMap](g)
           f.smartVectorize(maxCategoricalCardinality = MaxCategoricalCardinality,
-            numHashes = DefaultNumOfFeatures, autoDetectLanguage = TextTokenizer.AutoDetectLanguage,
-            minTokenLength = TextTokenizer.MinTokenLength, toLowercase = TextTokenizer.ToLowercase,
+            numHashes = DefaultNumOfFeatures, autoDetectLanguage = AutoDetectLanguage,
+            minTokenLength = MinTokenLength, toLowercase = ToLowercase,
             prependFeatureName = PrependFeatureName, cleanText = CleanText, cleanKeys = CleanKeys,
             others = other, trackNulls = TrackNulls)
         case t if t =:= weakTypeOf[URLMap] =>
@@ -285,7 +290,7 @@ private[op] case object Transmogrifier {
             others = other)
         case t if t =:= weakTypeOf[Phone] =>
           val (f, other) = castAs[Phone](g)
-          f.vectorize(defaultRegion = PhoneNumberParser.DefaultRegion, others = other)
+          f.vectorize(defaultRegion = DefaultRegion, others = other)
         case t if t =:= weakTypeOf[PickList] =>
           val (f, other) = castAs[PickList](g)
           f.vectorize(topK = TopK, minSupport = MinSupport, cleanText = CleanText, trackNulls = TrackNulls,
@@ -294,15 +299,15 @@ private[op] case object Transmogrifier {
           val (f, other) = castAs[Text](g)
           f.smartVectorize(maxCategoricalCardinality = MaxCategoricalCardinality,
             trackNulls = TrackNulls, numHashes = DefaultNumOfFeatures,
-            hashSpaceStrategy = defaults.HashSpaceStrategy, autoDetectLanguage = TextTokenizer.AutoDetectLanguage,
-            minTokenLength = TextTokenizer.MinTokenLength, toLowercase = TextTokenizer.ToLowercase,
+            hashSpaceStrategy = defaults.HashSpaceStrategy, autoDetectLanguage = AutoDetectLanguage,
+            minTokenLength = MinTokenLength, toLowercase = ToLowercase,
             prependFeatureName = PrependFeatureName, others = other)
         case t if t =:= weakTypeOf[TextArea] =>
           val (f, other) = castAs[TextArea](g)
           f.smartVectorize(maxCategoricalCardinality = MaxCategoricalCardinality,
             trackNulls = TrackNulls, numHashes = DefaultNumOfFeatures,
-            hashSpaceStrategy = defaults.HashSpaceStrategy, autoDetectLanguage = TextTokenizer.AutoDetectLanguage,
-            minTokenLength = TextTokenizer.MinTokenLength, toLowercase = TextTokenizer.ToLowercase,
+            hashSpaceStrategy = defaults.HashSpaceStrategy, autoDetectLanguage = AutoDetectLanguage,
+            minTokenLength = MinTokenLength, toLowercase = ToLowercase,
             prependFeatureName = PrependFeatureName, others = other)
         case t if t =:= weakTypeOf[URL] =>
           val (f, other) = castAs[URL](g)

diff --git a/docs/talks/index.md b/docs/talks/index.md
@@ -1,5 +1,9 @@
 # Talks
 
+**2019**
+* [Automated Machine Learning with TransmogrifAI](https://vaultanalytics.com/podcast/automated-machine-learning-with-transmogrifai/), Till Bergmann, Data Crunch Podcast
+* [Automated ML Pipelines For Unseen Customer Data](https://www.youtube.com/watch?v=IZyceNOSitI), Kevin Moore, PAPIs.io, [Slides](https://drive.google.com/file/d/1MStBS4tR1yuklCuDCrZHrejNAFk1j_k9/view)
+
 **2018**
 * [AutoML: The Assembly Line of Machine Learning](http://www.dataengconf.com/automl-the-assembly-line-of-machine-learning), Mayukh Bhaowal, DataEngConf
 * [The Black Swan of Perfectly Interpretable Models](https://www.infoq.com/presentations/salesforce-einstein-ml), Leah McGuire and Mayukh Bhaowal, QCon.ai