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amuelleramueller
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update notebook for renamed functions
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Lines changed: 33 additions & 35 deletions

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‎examples/OpenMLDemo.ipynb‎

Lines changed: 33 additions & 35 deletions
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@@ -118,7 +118,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"First 10 of 3335 datasets...\n",
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"First 10 of 2806 datasets...\n",
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" did name NumberOfInstances NumberOfFeatures\n",
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"0 1 anneal 898 39\n",
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"1 2 anneal 898 39\n",
@@ -361,7 +361,7 @@
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}
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],
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"source": [
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"X, y, attribute_names = dataset.get_dataset(target=dataset.default_target_attribute, return_attribute_names=True)\n",
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"X, y, attribute_names = dataset.get_data(target=dataset.default_target_attribute, return_attribute_names=True)\n",
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"iris = pd.DataFrame(X, columns=attribute_names)\n",
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"iris['class'] = y\n",
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"print(iris[:10])"
@@ -417,7 +417,7 @@
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],
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"source": [
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"dataset = openml.datasets.get_dataset(61)\n",
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"X, y = dataset.get_dataset(target=dataset.default_target_attribute)\n",
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"X, y = dataset.get_data(target=dataset.default_target_attribute)\n",
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"clf = ensemble.RandomForestClassifier()\n",
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"clf.fit(X, y)"
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]
@@ -464,7 +464,23 @@
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
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" max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
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" min_samples_leaf=1, min_samples_split=2,\n",
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" min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=1,\n",
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" oob_score=False, random_state=None, verbose=0,\n",
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" warm_start=False)"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"X_2d = X[:,2:4]\n",
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"clf.fit(X_2d, y)\n",
@@ -502,7 +518,7 @@
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}
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],
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"source": [
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"X, y, categorical = dataset.get_dataset(target=dataset.default_target_attribute,return_categorical_indicator=True)\n",
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"X, y, categorical = dataset.get_data(target=dataset.default_target_attribute,return_categorical_indicator=True)\n",
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"enc = preprocessing.OneHotEncoder(categorical_features=categorical)\n",
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"X = enc.fit_transform(X)\n",
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"clf.fit(X, y)"
@@ -537,16 +553,16 @@
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},
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"outputs": [
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{
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"ename": "TypeError",
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"evalue": "int() argument must be a string, a bytes-like object or a number, not 'NoneType'",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m<ipython-input-14-7653a7076e49>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mtask_list\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mopenml\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtasks\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlist_tasks\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[0mtasks\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtask_list\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"First 5 of %s tasks:\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtasks\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtasks\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'tid'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'did'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'name'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'task_type'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'estimation_procedure'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32m/home/andy/checkout/openml-python/openml/tasks/task_functions.py\u001b[0m in \u001b[0;36mlist_tasks\u001b[1;34m()\u001b[0m\n\u001b[0;32m 136\u001b[0m \u001b[0mthe\u001b[0m \u001b[0massociated\u001b[0m \u001b[0mdataset\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msome\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthese\u001b[0m \u001b[0mare\u001b[0m \u001b[0malso\u001b[0m \u001b[0mreturned\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 137\u001b[0m \"\"\"\n\u001b[1;32m--> 138\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_list_tasks\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'task/list'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 139\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 140\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32m/home/andy/checkout/openml-python/openml/tasks/task_functions.py\u001b[0m in \u001b[0;36m_list_tasks\u001b[1;34m(api_call)\u001b[0m\n\u001b[0;32m 160\u001b[0m \u001b[0mproc_dict\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'id'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mprocs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 161\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mtask_\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mtasks_dict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'oml:tasks'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'oml:task'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 162\u001b[1;33m task = {'tid': int(task_['oml:task_id']),\n\u001b[0m\u001b[0;32m 163\u001b[0m \u001b[1;34m'did'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtask_\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'oml:did'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 164\u001b[0m \u001b[1;34m'name'\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mtask_\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'oml:name'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;31mTypeError\u001b[0m: int() argument must be a string, a bytes-like object or a number, not 'NoneType'"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"First 5 of 8566 tasks:\n",
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" tid did name task_type estimation_procedure\n",
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"0 1 1 anneal Supervised Classification 10-fold Crossvalidation\n",
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"1 2 2 anneal Supervised Classification 10-fold Crossvalidation\n",
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"2 3 3 kr-vs-kp Supervised Classification 10-fold Crossvalidation\n",
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"3 4 4 labor Supervised Classification 10-fold Crossvalidation\n",
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"4 5 5 arrhythmia Supervised Classification 10-fold Crossvalidation\n"
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]
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}
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],
@@ -644,8 +660,8 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Uploaded run with id 538163\n",
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"Check it at www.openml.org/r/538163\n"
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"Uploaded run with id 538241\n",
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"Check it at www.openml.org/r/538241\n"
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]
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}
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],
@@ -667,24 +683,6 @@
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"source": [
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"More to come soon..."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {

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