MIT/FeatureLabs - update primitive and demo pipelines

v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/a8241394-4db0-4adf-a650-3e149a0af97c.yml → v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/0295a570-43ba-4320-bdb2-a0dadd700437.yml

-created: '2020-01-21T22:13:11.692820Z'
-digest: b6398d3cd5f77f8dbdb3f582493aa075fe628c2a06c3f47d698a178766f305f2
-id: a8241394-4db0-4adf-a650-3e149a0af97c
+created: '2020-01-22T20:53:55.879589Z'
+digest: 21c7baf2266c32785bdb5b92c5760d154e775a3283b19a0ef24297aab6ec4291
+id: 0295a570-43ba-4320-bdb2-a0dadd700437
 inputs:
 - name: inputs
 outputs:
-- data: steps.4.produce
+- data: steps.3.produce
   name: output predictions
 schema: https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json
 steps:
@@ -43,7 +43,7 @@ steps:
   outputs:
   - id: produce
   primitive:
-    digest: 0978d3fbc2847089e30112edfd6073d85f631f85b8382add7850df4d58640028
+    digest: bc83b41d0aac2b644dc4f42ebf97973669ddd2272fadd28fd442a67cb8fbff0a
     id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
     name: Multi Table Deep Feature Synthesis
     python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
@@ -53,23 +53,6 @@ steps:
     inputs:
       data: steps.1.produce
       type: CONTAINER
-  hyperparams:
-    use_semantic_types:
-      data: true
-      type: VALUE
-  outputs:
-  - id: produce
-  primitive:
-    digest: 1fbe6321949de3f9bd1d93c6900cd5c3b3ee4b1a01506b89c69a776a9d27bf7a
-    id: d016df89-de62-3c53-87ed-c06bb6a23cde
-    name: sklearn.impute.SimpleImputer
-    python_path: d3m.primitives.data_cleaning.imputer.SKlearn
-    version: 2019.11.13
-  type: PRIMITIVE
-- arguments:
-    inputs:
-      data: steps.2.produce
-      type: CONTAINER
     outputs:
       data: steps.1.produce
       type: CONTAINER
@@ -84,7 +67,7 @@ steps:
   type: PRIMITIVE
 - arguments:
     inputs:
-      data: steps.3.produce
+      data: steps.2.produce
       type: CONTAINER
     reference:
       data: steps.1.produce

v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/faa0ef1b-da85-4b6b-a592-a7d27dc226ec.yml → v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/0b41b4c0-a475-4cc1-95c2-b720f11c9220.yml

-created: '2020-01-21T22:09:54.245906Z'
-digest: cdd19e5c224e67d57ffaa4ead6706a6c4e70a47dec3ac058f550cfab4fd2d4fc
-id: faa0ef1b-da85-4b6b-a592-a7d27dc226ec
+created: '2020-01-22T20:50:45.826084Z'
+digest: 3233b184e2a511e1aeafbeeab51ee282b8de40e6a63b98f188b235fd23d48365
+id: 0b41b4c0-a475-4cc1-95c2-b720f11c9220
 inputs:
 - name: inputs
 outputs:
-- data: steps.5.produce
+- data: steps.4.produce
   name: output predictions
 schema: https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json
 steps:
@@ -65,10 +65,14 @@ steps:
     inputs:
       data: steps.1.produce
       type: CONTAINER
+  hyperparams:
+    max_features:
+      data: 10
+      type: VALUE
   outputs:
   - id: produce
   primitive:
-    digest: 0978d3fbc2847089e30112edfd6073d85f631f85b8382add7850df4d58640028
+    digest: bc83b41d0aac2b644dc4f42ebf97973669ddd2272fadd28fd442a67cb8fbff0a
     id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
     name: Multi Table Deep Feature Synthesis
     python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
@@ -78,23 +82,6 @@ steps:
     inputs:
       data: steps.2.produce
       type: CONTAINER
-  hyperparams:
-    use_semantic_types:
-      data: true
-      type: VALUE
-  outputs:
-  - id: produce
-  primitive:
-    digest: 1fbe6321949de3f9bd1d93c6900cd5c3b3ee4b1a01506b89c69a776a9d27bf7a
-    id: d016df89-de62-3c53-87ed-c06bb6a23cde
-    name: sklearn.impute.SimpleImputer
-    python_path: d3m.primitives.data_cleaning.imputer.SKlearn
-    version: 2019.11.13
-  type: PRIMITIVE
-- arguments:
-    inputs:
-      data: steps.3.produce
-      type: CONTAINER
     outputs:
       data: steps.2.produce
       type: CONTAINER
@@ -109,7 +96,7 @@ steps:
   type: PRIMITIVE
 - arguments:
     inputs:
-      data: steps.4.produce
+      data: steps.3.produce
       type: CONTAINER
     reference:
       data: steps.2.produce

v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/aae8edb2-ce99-4ec5-8533-b35b44450b40.yml → v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/4cae3eef-f76e-47fd-93a6-ea62ffd6481e.yml

-created: '2020-01-21T22:10:09.285081Z'
-digest: 7eb20df91f9a3c63dc9b49a88de98e109d14802cfe753ea0e083095a596b63b0
-id: aae8edb2-ce99-4ec5-8533-b35b44450b40
+created: '2020-01-22T20:50:31.025198Z'
+digest: e899bf8baddaee4e3179a0c0c87ce681f91e7de8a1425178a95e5cbf06993470
+id: 4cae3eef-f76e-47fd-93a6-ea62ffd6481e
 inputs:
 - name: inputs
 outputs:
-- data: steps.5.produce
+- data: steps.4.produce
   name: output predictions
 schema: https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json
 steps:
@@ -65,14 +65,10 @@ steps:
     inputs:
       data: steps.1.produce
       type: CONTAINER
-  hyperparams:
-    max_features:
-      data: 10
-      type: VALUE
   outputs:
   - id: produce
   primitive:
-    digest: 0978d3fbc2847089e30112edfd6073d85f631f85b8382add7850df4d58640028
+    digest: bc83b41d0aac2b644dc4f42ebf97973669ddd2272fadd28fd442a67cb8fbff0a
     id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
     name: Multi Table Deep Feature Synthesis
     python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
@@ -82,23 +78,6 @@ steps:
     inputs:
       data: steps.2.produce
       type: CONTAINER
-  hyperparams:
-    use_semantic_types:
-      data: true
-      type: VALUE
-  outputs:
-  - id: produce
-  primitive:
-    digest: 1fbe6321949de3f9bd1d93c6900cd5c3b3ee4b1a01506b89c69a776a9d27bf7a
-    id: d016df89-de62-3c53-87ed-c06bb6a23cde
-    name: sklearn.impute.SimpleImputer
-    python_path: d3m.primitives.data_cleaning.imputer.SKlearn
-    version: 2019.11.13
-  type: PRIMITIVE
-- arguments:
-    inputs:
-      data: steps.3.produce
-      type: CONTAINER
     outputs:
       data: steps.2.produce
       type: CONTAINER
@@ -113,7 +92,7 @@ steps:
   type: PRIMITIVE
 - arguments:
     inputs:
-      data: steps.4.produce
+      data: steps.3.produce
       type: CONTAINER
     reference:
       data: steps.2.produce

v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/1ddbccbb-70e1-417e-b2da-ba46a28ea0d9.yml → v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/6a3940c0-a510-405d-8dc8-a534357c91d1.yml

-created: '2020-01-21T22:11:26.455981Z'
-digest: 27a5a5a1c75bf3b75d04b028953506002998c316152ec0a1f24ab6ad4c078ea8
-id: 1ddbccbb-70e1-417e-b2da-ba46a28ea0d9
+created: '2020-01-22T20:52:05.232517Z'
+digest: c7acef854dddbfd338a6474e76209cbf5278e46f612a303644e5a9c638dc2af3
+id: 6a3940c0-a510-405d-8dc8-a534357c91d1
 inputs:
 - name: inputs
 outputs:
-- data: steps.4.produce
+- data: steps.3.produce
   name: output predictions
 schema: https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json
 steps:
@@ -43,7 +43,7 @@ steps:
   outputs:
   - id: produce
   primitive:
-    digest: 0978d3fbc2847089e30112edfd6073d85f631f85b8382add7850df4d58640028
+    digest: bc83b41d0aac2b644dc4f42ebf97973669ddd2272fadd28fd442a67cb8fbff0a
     id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
     name: Multi Table Deep Feature Synthesis
     python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
@@ -53,23 +53,6 @@ steps:
     inputs:
       data: steps.1.produce
       type: CONTAINER
-  hyperparams:
-    use_semantic_types:
-      data: true
-      type: VALUE
-  outputs:
-  - id: produce
-  primitive:
-    digest: 1fbe6321949de3f9bd1d93c6900cd5c3b3ee4b1a01506b89c69a776a9d27bf7a
-    id: d016df89-de62-3c53-87ed-c06bb6a23cde
-    name: sklearn.impute.SimpleImputer
-    python_path: d3m.primitives.data_cleaning.imputer.SKlearn
-    version: 2019.11.13
-  type: PRIMITIVE
-- arguments:
-    inputs:
-      data: steps.2.produce
-      type: CONTAINER
     outputs:
       data: steps.1.produce
       type: CONTAINER
@@ -84,7 +67,7 @@ steps:
   type: PRIMITIVE
 - arguments:
     inputs:
-      data: steps.3.produce
+      data: steps.2.produce
       type: CONTAINER
     reference:
       data: steps.1.produce

v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/5f86d57c-7d8c-437b-a77b-0ee1574d1d47.yml → v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/9cb27404-06eb-472a-a3db-63a51e4420c4.yml

-created: '2020-01-21T22:11:15.752763Z'
-digest: 6517d487fad35fb60ea9bc66954afbf03084902378a70f4e1b8adc8d52c190ab
-id: 5f86d57c-7d8c-437b-a77b-0ee1574d1d47
+created: '2020-01-22T20:55:49.956127Z'
+digest: d22f563b0d4ac4e42a96f6c0473705f2034e8c5f5d86d7be79a47086c3969b66
+id: 9cb27404-06eb-472a-a3db-63a51e4420c4
 inputs:
 - name: inputs
 outputs:
@@ -13,14 +13,11 @@ steps:
       data: inputs.0
       type: CONTAINER
   hyperparams:
-    fit_primitive:
-      data: 'no'
-      type: VALUE
     primitive:
       data:
-        case: transformer
+        case: unsupervised_learner
         value:
-          class: d3m.primitives.data_transformation.column_parser.Common
+          class: d3m.primitives.schema_discovery.profiler.Common
       type: VALUE
     resources:
       data:
@@ -40,38 +37,49 @@ steps:
     inputs:
       data: steps.0.produce
       type: CONTAINER
+  hyperparams:
+    fit_primitive:
+      data: 'no'
+      type: VALUE
+    primitive:
+      data:
+        case: transformer
+        value:
+          class: d3m.primitives.data_transformation.column_parser.Common
+      type: VALUE
+    resources:
+      data:
+        case: all
+        value: all
+      type: VALUE
   outputs:
   - id: produce
   primitive:
-    digest: 0978d3fbc2847089e30112edfd6073d85f631f85b8382add7850df4d58640028
-    id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
-    name: Multi Table Deep Feature Synthesis
-    python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
-    version: 0.7.2
+    digest: d564c75f0aebfb9cc70a808b11550cc199701e1a7d24d94b1c865aff233887d8
+    id: 5bef5738-1638-48d6-9935-72445f0eecdc
+    name: Map DataFrame resources to new resources using provided primitive
+    python_path: d3m.primitives.operator.dataset_map.DataFrameCommon
+    version: 0.1.0
   type: PRIMITIVE
 - arguments:
     inputs:
       data: steps.1.produce
       type: CONTAINER
-  hyperparams:
-    use_semantic_types:
-      data: true
-      type: VALUE
   outputs:
   - id: produce
   primitive:
-    digest: 1fbe6321949de3f9bd1d93c6900cd5c3b3ee4b1a01506b89c69a776a9d27bf7a
-    id: d016df89-de62-3c53-87ed-c06bb6a23cde
-    name: sklearn.impute.SimpleImputer
-    python_path: d3m.primitives.data_cleaning.imputer.SKlearn
-    version: 2019.11.13
+    digest: bc83b41d0aac2b644dc4f42ebf97973669ddd2272fadd28fd442a67cb8fbff0a
+    id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
+    name: Multi Table Deep Feature Synthesis
+    python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
+    version: 0.7.2
   type: PRIMITIVE
 - arguments:
     inputs:
       data: steps.2.produce
       type: CONTAINER
     outputs:
-      data: steps.1.produce
+      data: steps.2.produce
       type: CONTAINER
   outputs:
   - id: produce
@@ -87,7 +95,7 @@ steps:
       data: steps.3.produce
       type: CONTAINER
     reference:
-      data: steps.1.produce
+      data: steps.2.produce
       type: CONTAINER
   outputs:
   - id: produce

v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/e9a09b76-5cea-4184-adc0-8666da234501.yml → v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/a179a330-65e6-4b4a-93d7-61657954bcec.yml

-created: '2020-01-21T22:12:16.148578Z'
-digest: ddcaf2b03d54b7b68ae52b74a927b2700d84259dd35d4f4d7957852640215cea
-id: e9a09b76-5cea-4184-adc0-8666da234501
+created: '2020-01-22T20:52:55.925472Z'
+digest: 0405ab3a3f4edbee704f504c071db27c117d76c96c36a8040911e4a0abbb2704
+id: a179a330-65e6-4b4a-93d7-61657954bcec
 inputs:
 - name: inputs
 outputs:
@@ -13,14 +13,11 @@ steps:
       data: inputs.0
       type: CONTAINER
   hyperparams:
-    fit_primitive:
-      data: 'no'
-      type: VALUE
     primitive:
       data:
-        case: transformer
+        case: unsupervised_learner
         value:
-          class: d3m.primitives.data_transformation.column_parser.Common
+          class: d3m.primitives.schema_discovery.profiler.Common
       type: VALUE
     resources:
       data:
@@ -40,38 +37,49 @@ steps:
     inputs:
       data: steps.0.produce
       type: CONTAINER
+  hyperparams:
+    fit_primitive:
+      data: 'no'
+      type: VALUE
+    primitive:
+      data:
+        case: transformer
+        value:
+          class: d3m.primitives.data_transformation.column_parser.Common
+      type: VALUE
+    resources:
+      data:
+        case: all
+        value: all
+      type: VALUE
   outputs:
   - id: produce
   primitive:
-    digest: 0978d3fbc2847089e30112edfd6073d85f631f85b8382add7850df4d58640028
-    id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
-    name: Multi Table Deep Feature Synthesis
-    python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
-    version: 0.7.2
+    digest: d564c75f0aebfb9cc70a808b11550cc199701e1a7d24d94b1c865aff233887d8
+    id: 5bef5738-1638-48d6-9935-72445f0eecdc
+    name: Map DataFrame resources to new resources using provided primitive
+    python_path: d3m.primitives.operator.dataset_map.DataFrameCommon
+    version: 0.1.0
   type: PRIMITIVE
 - arguments:
     inputs:
       data: steps.1.produce
       type: CONTAINER
-  hyperparams:
-    use_semantic_types:
-      data: true
-      type: VALUE
   outputs:
   - id: produce
   primitive:
-    digest: 1fbe6321949de3f9bd1d93c6900cd5c3b3ee4b1a01506b89c69a776a9d27bf7a
-    id: d016df89-de62-3c53-87ed-c06bb6a23cde
-    name: sklearn.impute.SimpleImputer
-    python_path: d3m.primitives.data_cleaning.imputer.SKlearn
-    version: 2019.11.13
+    digest: bc83b41d0aac2b644dc4f42ebf97973669ddd2272fadd28fd442a67cb8fbff0a
+    id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
+    name: Multi Table Deep Feature Synthesis
+    python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
+    version: 0.7.2
   type: PRIMITIVE
 - arguments:
     inputs:
       data: steps.2.produce
       type: CONTAINER
     outputs:
-      data: steps.1.produce
+      data: steps.2.produce
       type: CONTAINER
   outputs:
   - id: produce
@@ -87,7 +95,7 @@ steps:
       data: steps.3.produce
       type: CONTAINER
     reference:
-      data: steps.1.produce
+      data: steps.2.produce
       type: CONTAINER
   outputs:
   - id: produce

v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/44130e38-85b2-4213-9922-86da63c2f42e.yml → v2020.1.9/MIT_FeatureLabs/d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization/0.7.2/pipelines/e6d54e1b-83d7-4817-a735-0b4aa96b3377.yml

-created: '2020-01-21T22:15:09.064516Z'
-digest: 877ab5873c4bcac47bb5943298876d226057f53f709918656fc1f415baaf939f
-id: 44130e38-85b2-4213-9922-86da63c2f42e
+created: '2020-01-22T20:51:55.092281Z'
+digest: 2b633c5ceb6bc20a7aa6486276aeaad9191ffcba2f667331e19aca014ce0da15
+id: e6d54e1b-83d7-4817-a735-0b4aa96b3377
 inputs:
 - name: inputs
 outputs:
-- data: steps.4.produce
+- data: steps.3.produce
   name: output predictions
 schema: https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json
 steps:
@@ -43,7 +43,7 @@ steps:
   outputs:
   - id: produce
   primitive:
-    digest: 0978d3fbc2847089e30112edfd6073d85f631f85b8382add7850df4d58640028
+    digest: bc83b41d0aac2b644dc4f42ebf97973669ddd2272fadd28fd442a67cb8fbff0a
     id: e659ef3a-f17c-4bbf-9e5a-13de79a4e55b
     name: Multi Table Deep Feature Synthesis
     python_path: d3m.primitives.feature_construction.deep_feature_synthesis.MultiTableFeaturization
@@ -53,23 +53,6 @@ steps:
     inputs:
       data: steps.1.produce
       type: CONTAINER
-  hyperparams:
-    use_semantic_types:
-      data: true
-      type: VALUE
-  outputs:
-  - id: produce
-  primitive:
-    digest: 1fbe6321949de3f9bd1d93c6900cd5c3b3ee4b1a01506b89c69a776a9d27bf7a
-    id: d016df89-de62-3c53-87ed-c06bb6a23cde
-    name: sklearn.impute.SimpleImputer
-    python_path: d3m.primitives.data_cleaning.imputer.SKlearn
-    version: 2019.11.13
-  type: PRIMITIVE
-- arguments:
-    inputs:
-      data: steps.2.produce
-      type: CONTAINER
     outputs:
       data: steps.1.produce
       type: CONTAINER
@@ -84,7 +67,7 @@ steps:
   type: PRIMITIVE
 - arguments:
     inputs:
-      data: steps.3.produce
+      data: steps.2.produce
       type: CONTAINER