From d854ba5d7d853275ae4764c2706d8f13dfd8386e Mon Sep 17 00:00:00 2001 From: Matthew Middlehurst Date: Wed, 25 Sep 2024 00:16:42 +0300 Subject: [PATCH] [DOC] Fix notebook failures (#2090) * skip seql * clustering --- .../classification/dictionary_based.ipynb | 1 + .../clustering/partitional_clustering.ipynb | 30 ++++--------------- 2 files changed, 6 insertions(+), 25 deletions(-) diff --git a/examples/classification/dictionary_based.ipynb b/examples/classification/dictionary_based.ipynb index b6af5ad752..ff9ae4eff0 100644 --- 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 index 5d123360af..58c4ccec29 100644 --- 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": {