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Questions tagged [one-hot-encoding]

One-Hot Encoding is a method to encode categorical variables to numerical data that Machine Learning algorithms can deal with. One-Hot encoding is most used during feature engineering for a ML Model. It converts categorical values into a new categorical column and assign a binary value of 1 or 0 to those columns.

Also known as Dummy Encoding, One-Hot Encoding is a method to encode categorical variables, where no such ordinal relationship exists, to numerical data that Machine Learning algorithms can deal with. One hot encoding is the most widespread approach, and it works very well unless your categorical variable takes on a large number of unique values. One hot encoding creates new, binary columns, indicating the presence of each possible value from the original data. These columns store ones and zeros for each row, indicating the categorical value of that row.

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Do I have to do one-hot-encoding separately for train and test dataset?

I'm working on a classification problem and I've split my data into train and test set. I have few categorical columns (around 4 -6) and I am thinking of using pd.get_dummies to convert my categorical values to OneHotEncoding. My question is do I…
Jeeth
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How can I one hot encode a list of strings with Keras?

I have a list: code = ['', 'are', 'defined', 'in', 'the', '"editable', 'parameters"', '\n', 'section.', '\n', 'A', 'larger', '`tsteps`', 'value', 'means', 'that', 'the', 'LSTM', 'will', 'need', 'more', 'memory', '\n', 'to', 'figure', 'out'] And…
Shamoon
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Why does Spark's OneHotEncoder drop the last category by default?

I would like to understand the rational behind the Spark's OneHotEncoder dropping the last category by default. For example: >>> fd = spark.createDataFrame( [(1.0, "a"), (1.5, "a"), (10.0, "b"), (3.2, "c")], ["x","c"]) >>> ss =…
Corey
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Handling unknown values for label encoding

How can I handle unknown values for label encoding in sk-learn? The label encoder will only blow up with an exception that new labels were detected. What I want is the encoding of categorical variables via one-hot-encoder. However, sk-learn does not…
Georg Heiler
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R - How to one hot encoding a single column while keep other columns still?

I have a data frame like this: group student exam_passed subject A 01 Y Math A 01 N Science A 01 Y Japanese A 02 N Math A 02 Y Science B …
J.D
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How to interpret results of Spark OneHotEncoder

I read the OHE entry from Spark docs, One-hot encoding maps a column of label indices to a column of binary vectors, with at most a single one-value. This encoding allows algorithms which expect continuous features, such as Logistic Regression, to…
Maria
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Train multi-class image classifier in Keras

I was following a tutorial to learn train a classifier using Keras https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html Specifically, from the second script given by the author, I wanted to transform the…
PIZZA PIZZA
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How do you decode one-hot labels in Tensorflow?

Been looking, but can't seem to find any examples of how to decode or convert back to a single integer from a one-hot value in TensorFlow. I used tf.one_hot and was able to train my model but am a bit confused on how to make sense of the label after…
Matt Camp
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scikit-learn: How to compose LabelEncoder and OneHotEncoder with a pipeline?

While preprocessing the labels for a machine learning classifying task, I need to one hot encode the labels which take string values. It happens that OneHotEncoder from sklearn.preprocessing or to_categorical from kera.np_utils require int inputs.…
Learning is a mess
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Julia DataFrames - How to do one-hot encoding?

I'm using Julia's DataFrames.jl package. In it, I have a dataframe with a columns containing a list of strings (e.g. ["Type A", "Type B", "Type D"]). How does one then performs a one-hot encoding? I wasn't able to find a pre-built function in the…
Davi Barreira
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ValueError: Shape mismatch: if categories is an array, it has to be of shape (n_features,)

I have create a simple code to implement OneHotEncoder. from sklearn.preprocessing import OneHotEncoder X = [[0, 'a'], [0, 'b'], [1, 'a'], [2, 'b']] onehotencoder = OneHotEncoder(categories=[0]) X = onehotencoder.fit_transform(X).toarray() I just…
arga wirawan
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Tensorflow InvalidArgumentError (indices) while training with Keras

I'm trying to train a LSTM network on some data, unfortunately I keep running into following error: InvalidArgumentError: indices[] = is not in [0, 4704) Train on 180596 samples, validate on 45149 samples Epoch…
matm
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SciKit-Learn Label Encoder resulting in error 'argument must be a string or number'

I'm a bit confused - creating an ML model here. I'm at the step where I'm trying to take categorical features from a "large" dataframe (180 columns) and one-hot them so that I can find the correlation between the features and select the "best"…
mikelowry
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OneHotEncoder - encoding only some of categorical variable columns

Let's assume that I have a pandas dataframe with the following column names: 'age' (e.g. 33, 26, 51 etc) 'seniority' (e.g. 'junior', 'senior' etc) 'gender' (e.g. 'male', 'female') 'salary' (e.g. 32000, 40000, 64000 etc) I want to transform the…
Outcast
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Avoiding Dummy variable trap and neural network

I know that categorical data should be one-hot encoded before training the machine learning algorithm. I also need that for multivariate linear regression I need to exclude one of the encoded variable to avoid so called dummy variable trap. Ex: If I…
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