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Fix spelling/grammar in pipeline notebook #1082

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12 changes: 6 additions & 6 deletions notebooks/02 sklearn Pipeline.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -116,9 +116,9 @@
" \n",
"Here comes the tricky part!\n",
" \n",
"The input to the pipeline will be our dataframe `X`, which one row per identifier.\n",
"The input to the pipeline will be our dataframe `X`, with one row per identifier.\n",
"It is currently empty.\n",
"But which time series data should the `RelevantFeatureAugmenter` to actually extract the features from?\n",
"But which time series data should the `RelevantFeatureAugmenter` use to actually extract the features from?\n",
"\n",
"We need to pass the time series data (stored in `df_ts`) to the transformer.\n",
" \n",
Expand Down Expand Up @@ -179,7 +179,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"During interference, the augmentor does only extract the relevant features it has found out in the training phase and the classifier predicts the target using these features."
"During inference, the augmenter only extracts those features that it has found as being relevant in the training phase. The classifier predicts the target using these features."
]
},
{
Expand Down Expand Up @@ -211,7 +211,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also find out, which columns the augmenter has selected"
"You can also find out which columns the augmenter has selected"
]
},
{
Expand Down Expand Up @@ -248,11 +248,11 @@
"metadata": {},
"source": [
"In the example above we passed in a single `df_ts` into the `RelevantFeatureAugmenter`, which was used both for training and predicting.\n",
"During training, only the data with the `id`s from `X_train` where extracted and during prediction the rest.\n",
"During training, only the data with the `id`s from `X_train` were extracted. The rest of the data are extracted during prediction.\n",
"\n",
"However, it is perfectly fine to call `set_params` twice: once before training and once before prediction. \n",
"This can be handy if you for example dump the trained pipeline to disk and re-use it only later for prediction.\n",
"You only need to make sure that the `id`s of the enteties you use during training/prediction are actually present in the passed time series data."
"You only need to make sure that the `id`s of the entities you use during training/prediction are actually present in the passed time series data."
]
},
{
Expand Down
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