change svm kernel

.dvc/config

@@ -1,7 +1,9 @@
 [core]
     autostage = true
-    remote = read-write
+    remote = datastore
 ['remote "read"']
     url = https://winequality-red.s3.amazonaws.com/
 ['remote "read-write"']
-    url = s3://winequality-red/
+    url = s3://darkhorse-ar-card/
+['remote "datastore"']
+    url = s3://darkhorse-static-data

dvc.lock

@@ -43,6 +43,7 @@ stages:
           hyperparameters:
             svm__kernel:
             - linear
+            - rbf
             svm__C:
             - 0.1
             - 1
@@ -57,10 +58,10 @@ stages:
             verbose: 3
     outs:
     - path: model/svm
-      md5: ba0c50b412f6b5d5c5bd6c0ef163b1a1
-      size: 148163
+      md5: 56a719e06202368c953540a7cb3e37ef
+      size: 142616
     - path: model/svm.mlem
-      md5: 3e7f2947de87d4500fb0dff8c1311555
+      md5: b562c8482a0cb77f10bf8b14bf65f548
       size: 1263
   evaluate:
     cmd: python src/evaluate.py
@@ -70,8 +71,8 @@ stages:
       size: 194875
       nfiles: 4
     - path: model/svm
-      md5: ba0c50b412f6b5d5c5bd6c0ef163b1a1
-      size: 148163
+      md5: 56a719e06202368c953540a7cb3e37ef
+      size: 142616
     - path: src/evaluate.py
       md5: 912aac9c6e00b70858f1d47bd16e51a0
       size: 803
@@ -83,5 +84,5 @@ stages:
         model: model/svm
     outs:
     - path: dvclive/metrics.json
-      md5: d71ae0196bba8e553dbad618e306517b
-      size: 28
+      md5: 62b3730eec31d2778145d46759a8a45f
+      size: 27

dvclive/params.yaml

@@ -1,4 +1,4 @@
 Best hyperparameters:
-  svm__C: 10
+  svm__C: 1
   svm__gamma: 0.1
-  svm__kernel: linear
+  svm__kernel: rbf

dvclive/plots/metrics/accuracy.tsv

@@ -1,2 +1,2 @@
 step	accuracy
-0	0.559375
+0	0.60625

dvclive/report.html

@@ -22,10 +22,10 @@
             <div style="display: flex;justify-content: center;">
                 <table>
 <thead>
-<tr><th>Best hyperparameters                                      </th></tr>
+<tr><th>Best hyperparameters                                  </th></tr>
 </thead>
 <tbody>
-<tr><td>{&#x27;svm__C&#x27;: 10, &#x27;svm__gamma&#x27;: 0.1, &#x27;svm__kernel&#x27;: &#x27;linear&#x27;}</td></tr>
+<tr><td>{&#x27;svm__C&#x27;: 1, &#x27;svm__gamma&#x27;: 0.1, &#x27;svm__kernel&#x27;: &#x27;rbf&#x27;}</td></tr>
 </tbody>
 </table>
             </div>
@@ -39,15 +39,15 @@
 <tr><th style="text-align: right;">  accuracy</th></tr>
 </thead>
 <tbody>
-<tr><td style="text-align: right;">  0.559375</td></tr>
+<tr><td style="text-align: right;">   0.60625</td></tr>
 </tbody>
 </table>
             </div>
         </div>
 
     <div id = "static_accuracy">
         <script type = "text/javascript">
-            var spec = {"$schema": "https://vega.github.io/schema/vega-lite/v5.json", "data": {"values": [{"step": "0", "accuracy": "0.559375", "rev": "workspace"}]}, "title": "accuracy", "width": 300, "height": 300, "params": [{"name": "smooth", "value": 0.001, "bind": {"input": "range", "min": 0.001, "max": 1, "step": 0.001}}], "layer": [{"mark": "line", "encoding": {"x": {"field": "step", "type": "quantitative", "title": "step"}, "y": {"field": "accuracy", "type": "quantitative", "title": "accuracy", "scale": {"zero": false}}, "color": {"field": "rev", "type": "nominal"}}, "transform": [{"loess": "accuracy", "on": "step", "groupby": ["rev", "filename", "field", "filename::field"], "bandwidth": {"signal": "smooth"}}]}, {"mark": {"type": "point", "tooltip": {"content": "data"}}, "encoding": {"x": {"field": "step", "type": "quantitative", "title": "step"}, "y": {"field": "accuracy", "type": "quantitative", "title": "accuracy", "scale": {"zero": false}}, "color": {"field": "rev", "type": "nominal"}}}]};
+            var spec = {"$schema": "https://vega.github.io/schema/vega-lite/v5.json", "data": {"values": [{"step": "0", "accuracy": "0.60625", "rev": "workspace"}]}, "title": "accuracy", "width": 300, "height": 300, "params": [{"name": "smooth", "value": 0.001, "bind": {"input": "range", "min": 0.001, "max": 1, "step": 0.001}}], "layer": [{"mark": "line", "encoding": {"x": {"field": "step", "type": "quantitative", "title": "step"}, "y": {"field": "accuracy", "type": "quantitative", "title": "accuracy", "scale": {"zero": false}}, "color": {"field": "rev", "type": "nominal"}}, "transform": [{"loess": "accuracy", "on": "step", "groupby": ["rev", "filename", "field", "filename::field"], "bandwidth": {"signal": "smooth"}}]}, {"mark": {"type": "point", "tooltip": {"content": "data"}}, "encoding": {"x": {"field": "step", "type": "quantitative", "title": "step"}, "y": {"field": "accuracy", "type": "quantitative", "title": "accuracy", "scale": {"zero": false}}, "color": {"field": "rev", "type": "nominal"}}}]};
             vegaEmbed('#static_accuracy', spec);
         </script>
     </div>

model/svm.mlem

@@ -1,7 +1,7 @@
 artifacts:
   data:
-    hash: ba0c50b412f6b5d5c5bd6c0ef163b1a1
-    size: 148163
+    hash: 56a719e06202368c953540a7cb3e37ef
+    size: 142616
     uri: svm
 call_orders:
   predict:

params.yaml

@@ -9,6 +9,7 @@ train:
   hyperparameters:
     svm__kernel:
     - linear
+    - rbf
     svm__C:
     - 0.1
     - 1