sklearn-crfsuite | scikit-learn inspired API for CRFsuite | Machine Learning library
kandi X-RAY | sklearn-crfsuite Summary
kandi X-RAY | sklearn-crfsuite Summary
scikit-learn inspired API for CRFsuite
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Top functions reviewed by kandi - BETA
- Wraps a function to flattens y
- Return a flattened version of yaml
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sklearn-crfsuite Examples and Code Snippets
Community Discussions
Trending Discussions on sklearn-crfsuite
QUESTION
I have built a Sentence Boundary Detection Classifier. For the sequence labeling I used a conditional random field. For the hyperparameter optimization I would like to use RandomizedSearchCV. My training data consists of 6 annotated texts. I merge all 6 texts to a tokenlist. For the implementation I followed an example from the documentation. Here my simplified code:
...ANSWER
Answered 2022-Jan-31 at 13:33According to the official tutorial here, your train/test sets (i.e., X_train
, X_test
) should be a list of lists of dictionaries. For example:
QUESTION
i have been using rasa for the past few weeks without problems. But recently i had issues with the installation of Spacy, leading me to uninstall an reinstall python. The issue may have occurred because of some dualities between python3.8 and 3.9 which i wasnt abled to pinpoint.
After deleting all python version from my computer, i just reinstalled python 3.9.2. and reinstall rasa with:
...ANSWER
Answered 2021-Mar-21 at 14:59rasa
2.4 declares compatibility with Python 3.6, 3.7 and 3.8 but not 3.9 so pip
is trying to find one compatible with 3.9 or at least one that doesn't declare any restriction. It finds such release at version 0.0.5.
To use rasa
2.4 downgrade to Python 3.8.
PS. Don't hurry up to upgrade to the latest Python — 3rd-party packages are usually not so fast. Currently Python 3.7 and 3.8 are the best.
QUESTION
I have exactly the same problem as mentioned in PIP install rasa-x takes forever. In the Rasa installation guide they say, you have to create an environment first. Everytime I do: conda create --name rasa python==3.7.6
it automatically downloads pip-20.3.3. If I now try the pip install --upgrade pip==20.2
command it shows the following error: Error. What did I do wrong? Thanks for the help!
**Update: python -m pip install --upgrade pip==20.2
worked, but now there is another problem when trying to install Rasa-X:Rasa-X installation error
here is the code
...ANSWER
Answered 2021-Jan-25 at 13:34I had this issue as well and for me installing pip packages with python -m pip install
worked. So python -m pip install --upgrade pip==20.2
should work for you.
See here:
QUESTION
I successfully installed scikit-learn 0.23.1 with pip.
...ANSWER
Answered 2020-Jul-06 at 10:17I discovered that I have two versions of python, the first is included in anaconda and the second outside of anaconda I solved the problem by:
- uninstall of two versions
- installation only anaconda
QUESTION
When I tried this code:
...ANSWER
Answered 2020-May-14 at 05:51grid_scores_
is deprecated and cv_results_
is used now.
For more reference RandomizedSearchCV
QUESTION
I'm trying to create an annotations prediction model, following the tutorial here, but my model doesn't learn anything. Here is a sample of my training data and labels:
[{'bias': 1.0, 'word.lower()': '\nreference\nissue\ndate\ndgt86620\n4\n \n19-dec-05\nfalcon\n7x\ntype\ncertification\n27_4-100\nthis\ndocument\nis\nthe\nintellectual\nprop...nairbrakes\nhandle\nposition\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n0\ntable\n1\n:\nairbrake\ncas\nmessages\n', 'word[-3:]': 'es\n', 'word[-2:]': 's\n', 'word.isupper()': False, 'word.istitle()': False, 'word.isdigit()': False, 'postag': 'POS', 'postag[:2]': 'PO', 'w_emb_0': 0.03418987928976114, 'w_emb_1': 0.617338281 1066742, 'w_emb_2': 0.004420982990809508, 'w_emb_3': 0.08293022662242588, 'w_emb_4': 0.22162269482070363, 'w_emb_5': 0.4334545347397811, 'w_emb_6': 0.7844891779932379, 'w_emb_7': 0.028043262790094503, 'w_emb_8': 0.5233847386564157, 'w_emb_9': 0.9685677133128328, 'w_em b_10': 0.19379126558708126, 'w_emb_11': 0.2809608896964926, 'w_emb_12': 0.384759230815804, 'w_emb_13': 0.15385904662767336, 'w_emb_14': 0.5206500040610533, 'w_emb_15': 0.009148526006733215, 'w_emb_16': 0.5894118695171416, 'w_emb_17': 0.7356989708459056, 'w_emb_18': 0. 5576774100159024, 'w_emb_19': 0.2185294430010376, 'BOS': True, '+1:word.lower()': 'reference', '+1:word.istitle()': False, '+1:word.isupper()': True, '+1:postag': 'POS', '+1:postag[:2]': 'PO'}, {'bias': 1.0, 'word.lower()': 'reference', 'word[-3:]': 'NCE', 'word[-2:]' : 'CE', 'word.isupper()': True, 'word.istitle()': False, 'word.isdigit()': False, 'postag': 'POS', 'postag[:2]': 'PO', 'w_emb_0': -0.390038, 'w_emb_1': 0.30677223, 'w_emb_2': -1.010975, 'w_emb_3': 0.3656154, 'w_emb_4': 0.5319459, 'w_emb_5': 0.45572615, 'w_emb_6': -0.4 6090943, 'w_emb_7': 0.87250936, 'w_emb_8': 0.036648277, 'w_emb_9': -0.3057043, 'w_emb_10': 0.33427167, 'w_emb_11': -0.19664396, 'w_emb_12': -0.64899784, 'w_emb_13': -0.1785065, 'w_emb_14': -0.117423356, 'w_emb_15': 0.16247013, 'w_emb_16': 0.11694676, 'w_emb_17': -0.30 693895, 'w_emb_18': -1.0026807, 'w_emb_19': 0.9946743, '-1:word.lower()': '\nreference...n \n \n \n \n \n \n \n \n0\ntable\n1\n:\nairbrake\ncas\nmessages\n', '-1:word.istitle()': False, '-1:word.isupper()': False, '-1:postag': 'POS', '-1:postag[:2]': 'PO', '+1:word.lower()': 'issue', '+1:word.istitle()': False, '+1:word. isupper()': True, '+1:postag': 'POS', '+1:postag[:2]': 'PO'}, {'bias': 1.0, 'word.lower()': 'issue', 'word[-3:]': 'SUE', 'word[-2:]': 'UE', 'word.isupper()': True, 'word.istitle()': False, 'word.isdigit()': False, 'postag': 'POS', 'postag[:2]': 'PO', 'w_emb_0': -1.220 4882, 'w_emb_1': 0.8920707, 'w_emb_2': -3.8380668, 'w_emb_3': 1.5641377, 'w_emb_4': 2.1918254, 'w_emb_5': 1.8509868, 'w_emb_6': -2.0664182, 'w_emb_7': 3.1591077, 'w_emb_8': -0.33126026, 'w_emb_9': -1.4278139, 'w_emb_10': 0.9291533, 'w_emb_11': -0.6761407, 'w_emb_12': -2.9582167, 'w_emb_13': -0.5395561, 'w_emb_14': -0.8363763, 'w_emb_15': 0.25568742, 'w_emb_16': 0.4932978, 'w_emb_17': -1.6198335, 'w_emb_18': -4.183924, 'w_emb_19': 4.281094, '-1:word.lower()': 'reference', '-1:word.istitle()': False, '-1:word.isupper()': True, '-1:p ostag': 'POS', '-1:postag[:2]': 'PO', '+1:word.lower()': 'date', '+1:word.istitle()': False, '+1:word.isupper()': True, '+1:postag': 'POS', '+1:postag[:2]': 'PO'}...]
y_train = ['O', 'O', 'O'...'I-data-c-a-s_message-type'....'B-data-c-a-s_message-type']
and here is the model definition and training:
`
...ANSWER
Answered 2020-Apr-01 at 09:15The problem is solved. As you can see above, the support (number of evaluation samples) is a total of 113. However, the number of samples in the training set was just about 14 !! which is too small ! and I've just not noticed this difference. I've inverted the training and test datasets, and now, performances are something like this:
QUESTION
I'm using the rasa nlu with the supervised_embedding pipeline, and I am trying to train my models. On my local machine, I can train without any issues. When I try to train the models on my server, I am getting the following error:
...ANSWER
Answered 2020-Feb-26 at 14:31Looks like the reason it wasn't working on the server is because the CPU on it doesn't have the AVX instruction set. I have managed to train it on another server that has the AVX instruction set.
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Install sklearn-crfsuite
You can use sklearn-crfsuite like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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