[DOC] Fix notebook failures (#2090)

* skip seql * clustering
aeon-toolkit · Sep 24, 2024 · d854ba5 · d854ba5
1 parent 807a6e8
commit d854ba5
Show file tree

Hide file tree

Showing 2 changed files with 6 additions and 25 deletions.
diff --git a/examples/classification/dictionary_based.ipynb b/examples/classification/dictionary_based.ipynb
@@ -420,6 +420,7 @@
     "names.remove(\"MUSE\")  # Multivariate classifier\n",
     "names.remove(\"OrdinalTDE\")  # Ordinal classifier\n",
     "names.remove(\"REDCOMETS\")  # We still need to evaluate this classifier\n",
+    "names.remove(\"MrSEQLClassifier\")  # We still need to evaluate this classifier\n",
     "\n",
     "results, present_names = get_estimator_results_as_array(\n",
     "    names, univariate, include_missing=False\n",

diff --git a/examples/clustering/partitional_clustering.ipynb b/examples/clustering/partitional_clustering.ipynb
@@ -147,8 +147,7 @@
    ],
    "metadata": {
     "collapsed": false
-   },
-   "outputs": []
+   }
   },
   {
    "cell_type": "code",
@@ -211,8 +210,7 @@
    ],
    "metadata": {
     "collapsed": false
-   },
-   "outputs": []
+   }
   },
   {
    "cell_type": "markdown",
@@ -629,7 +627,7 @@
    "source": [
     "k_medoids = TimeSeriesKMedoids(\n",
     "    n_clusters=2,  # Number of desired centers\n",
-    "    init=\"random\",  # Center initialisation technique\n",
+    "    init_algorithm=\"random\",  # Center initialisation technique\n",
     "    max_iter=10,  # Maximum number of iterations for refinement on training set\n",
     "    verbose=False,  # Verbose\n",
     "    distance=\"dtw\",  # Distance to use\n",
@@ -708,7 +706,7 @@
    "source": [
     "k_medoids = TimeSeriesKMedoids(\n",
     "    n_clusters=2,  # Number of desired centers\n",
-    "    init=\"random\",  # Center initialisation technique\n",
+    "    init_algorithm=\"random\",  # Center initialisation technique\n",
     "    max_iter=10,  # Maximum number of iterations for refinement on training set\n",
     "    distance=\"msm\",  # Distance to use\n",
     "    random_state=1,\n",
@@ -794,7 +792,7 @@
    "source": [
     "k_medoids = TimeSeriesKMedoids(\n",
     "    n_clusters=2,  # Number of desired centers\n",
-    "    init=\"random\",  # Center initialisation technique\n",
+    "    init_algorithm=\"random\",  # Center initialisation technique\n",
     "    max_iter=10,  # Maximum number of iterations for refinement on training set\n",
     "    distance=\"msm\",  # Distance to use\n",
     "    random_state=1,\n",
@@ -1071,24 +1069,6 @@
    "metadata": {
     "collapsed": false
    }
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "outputs": [],
-   "source": [],
-   "metadata": {
-    "collapsed": false
-   }
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "outputs": [],
-   "source": [],
-   "metadata": {
-    "collapsed": false
-   }
   }
  ],
  "metadata": {