model: scikit: Simple Linear Regression

Signed-off-by: John Andersen <[email protected]>

.travis.yml

@@ -16,6 +16,7 @@ env:
   - PLUGIN=.
   - PLUGIN=model/tensorflow
   - PLUGIN=model/scratch
+  - PLUGIN=model/scikit
   - PLUGIN=feature/git
   - PLUGIN=feature/auth
   - CHANGELOG=1

CHANGELOG.md

@@ -21,6 +21,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   `argparse.ArgumentParser` via the `CLI_FORMATTER_CLASS` property.
 - Skeleton for service creation was added
 - Simple Linear Regression model from scratch
+- Scikit Linear Regression model
 - Community link in CONTRIBUTING.md.
 - Explained three main parts of DFFML on docs homepage
 - Documentation on how to use ML models on docs Models plugin page.

docs/plugins/dffml_model.rst

@@ -220,6 +220,90 @@ hash of their feature names.
   - default: /home/user/.cache/dffml/scratch
   - Directory where state should be saved
 
+- predict: String
+
+  - Label or the value to be predicted
+
+dffml_model_scikit
+------------------
+
+.. code-block:: console
+
+    pip install dffml-model-scikit
+
+
+scikitlr
+~~~~~~~~
+
+*Core*
+
+Linear Regression Model implemented using scikit. Models are saved under the
+``directory`` in subdirectories named after the hash of their feature names.
+
+.. code-block:: console
+
+    $ cat > train.csv << EOF
+    Years,Expertise,Trust,Salary
+    0,1,0.2,10
+    1,3,0.4,20
+    2,5,0.6,30
+    3,7,0.8,40
+    EOF
+    $ cat > test.csv << EOF
+    Years,Expertise,Trust,Salary
+    4,9,1.0,50
+    5,11,1.2,60
+    EOF
+    $ dffml train \
+        -model scikitlr \
+        -features def:Years:int:1 def:Expertise:int:1 def:Trust:float:1 \
+        -model-predict Salary \
+        -sources f=csv \
+        -source-filename train.csv \
+        -source-readonly \
+        -log debug
+    $ dffml accuracy \
+        -model scikitlr \
+        -features def:Years:int:1 def:Expertise:int:1 def:Trust:float:1 \
+        -model-predict Salary \
+        -sources f=csv \
+        -source-filename test.csv \
+        -source-readonly \
+        -log debug
+    1.0
+    $ echo -e 'Years,Expertise,Trust\n6,13,1.4\n' | \
+      dffml predict all \
+        -model scikitlr \
+        -features def:Years:int:1 def:Expertise:int:1 def:Trust:float:1 \
+        -model-predict Salary \
+        -sources f=csv \
+        -source-filename /dev/stdin \
+        -source-readonly \
+        -log debug
+    [
+        {
+            "extra": {},
+            "features": {
+                "Expertise": 13,
+                "Trust": 1.4,
+                "Years": 6
+            },
+            "last_updated": "2019-07-31T08:40:59Z",
+            "prediction": {
+                "confidence": 1.0,
+                "value": 70.0
+            },
+            "src_url": "0"
+        }
+    ]
+
+**Args**
+
+- directory: String
+
+  - default: /home/user/.cache/dffml/scikit
+  - Directory where state should be saved
+
 - predict: String
 
   - Label or the value to be predicted

model/scikit/.coveragerc

@@ -0,0 +1,13 @@
+[run]
+source =
+    dffml_model_scikit
+    tests
+branch = True
+
+[report]
+exclude_lines =
+    no cov
+    no qa
+    noqa
+    pragma: no cover
+    if __name__ == .__main__.:

model/scikit/.gitignore

@@ -0,0 +1,20 @@
+*.log
+*.pyc
+.cache/
+.coverage
+.idea/
+.vscode/
+*.egg-info/
+build/
+dist/
+docs/build/
+venv/
+wheelhouse/
+*.egss
+.mypy_cache/
+*.swp
+.venv/
+.eggs/
+*.modeldir
+*.db
+htmlcov/

model/scikit/LICENSE

@@ -0,0 +1,21 @@
+Copyright (c) 2019 Intel
+
+MIT License
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

model/scikit/MANIFEST.in

@@ -0,0 +1,2 @@
+include README.md
+include LICENSE

model/scikit/README.md

@@ -0,0 +1,71 @@
+# DFFML Models For scikit / sklearn
+
+## About
+
+Models created using scikit.
+
+## Install
+
+```console
+python3.7 -m pip install --user dffml-model-scikit
+```
+
+## Usage
+
+1. Linear Regression Model
+
+For implementing linear regression to a dataset, let us take a simple example:
+
+| Years of Experience  |  Expertise | Trust Factor | Salary |
+| -------------------- | ---------- | ------------ | ------ |
+|          0           |     01     |      0.2     |   10   |
+|          1           |     03     |      0.4     |   20   |
+|          2           |     05     |      0.6     |   30   |
+|          3           |     07     |      0.8     |   40   |
+|          4           |     09     |      1.0     |   50   |
+|          5           |     11     |      1.2     |   60   |
+
+```console
+$ cat > train.csv << EOF
+Years,Expertise,Trust,Salary
+0,1,0.2,10
+1,3,0.4,20
+2,5,0.6,30
+3,7,0.8,40
+EOF
+$ cat > test.csv << EOF
+Years,Expertise,Trust,Salary
+4,9,1.0,50
+5,11,1.2,60
+EOF
+$ dffml train \
+    -model scikitlr \
+    -features def:Years:int:1 def:Expertise:int:1 def:Trust:float:1 \
+    -model-predict Salary \
+    -sources f=csv \
+    -source-filename train.csv \
+    -source-readonly \
+    -log debug
+$ dffml accuracy \
+    -model scikitlr \
+    -features def:Years:int:1 def:Expertise:int:1 def:Trust:float:1 \
+    -model-predict Salary \
+    -sources f=csv \
+    -source-filename test.csv \
+    -source-readonly \
+    -log debug
+$ echo -e 'Years,Expertise,Trust\n6,13,1.4\n' | \
+  dffml predict all \
+    -model scikitlr \
+    -features def:Years:int:1 def:Expertise:int:1 def:Trust:float:1 \
+    -model-predict Salary \
+    -sources f=csv \
+    -source-filename /dev/stdin \
+    -source-readonly \
+    -log debug
+```
+
+## License
+
+Scikit Models are distributed under the terms of the
+[MIT License](LICENSE).