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     1  ~ 2014 sep 12skitlearnscikit-learn: machine learning in Python — scikit-learn 0.15.2 scikit-learn. Machine Learning in Python. Simple and efficient tools for data mining and data analysis; Accessible to everybody, and reusable in various contexts 
     1  ~ 2014 aug 23machine learning tutorialAn introduction to machine learning with scikit-learn — scikit-learn Section contents. In this section, we introduce the machine learning vocabulary that we use through-out scikit-learn and give a simple learning example.
     1  +2 2014 aug 22vector toystore header5. Dataset loading utilities — scikit-learn 0.15.1 documentationThe toy datasets as well as the 'real world' datasets and the datasets fetched from mldata.org .... Vectorizer with custom parameters so as to extract feature vectors . .... things that appear in the 20 Newsgroups data, such as newsgroup headers .
     1  ~ 2014 aug 10machine learning pythonscikit-learn: machine learning in Python — scikit-learn 0.15.1 scikit-learn. Machine Learning in Python . Simple and efficient tools for data mining and data analysis; Accessible to everybody, and reusable in various contexts ... ‎Installation - ‎Documentation - ‎1. Supervised learning - ‎Examples
     1  +1 2014 jul 17text clustering pythonClustering text documents using k-means — scikit-learn 0.14.1 Python source code: document_clustering .py ... from sklearn.decomposition import TruncatedSVD from sklearn.feature_extraction. text import TfidfVectorizer from ...
     3  +3 2014 jul 23decision tree learning1.8. Decision Trees — scikit- learn 0.15.0 documentationFor instance, in the example below, decision trees learn from data to approximate a sine curve with a set of if-then-else decision rules. The deeper the tree, the ...
     4  -1 2014 oct 03irregular choice skl1.4. Nearest Neighbors — scikit-learn 0.15.2 documentationsklearn .neighbors provides functionality for unsupervised and supervised ... general, be any metric measure: standard Euclidean distance is the most common choice . ... in classification situations where the decision boundary is very irregular .
     5  +1 2014 sep 24clustering algorithms2.3. Clustering — scikit-learn 0.15.2 documentationEach clustering algorithm comes in two variants: a class, that implements the fit method to learn the clusters on train data, and a function, that, given train data, ...
     5  -1 2014 sep 03confusion matrixConfusion matrix — scikit-learn 0.15.1 documentationExample of confusion matrix usage to evaluate the quality of the output of a classifier on the iris data set. The diagonal elements represent the number of points ...
     5  ~ 2014 aug 23score function python3.5. Model evaluation: quantifying the quality of predictions — scikit That function converts score functions (discussed below in Function for ... is to build a completely new and custom scorer object from a simple python function :.
     5  +5 2014 aug 15receiver operating characteristicReceiver Operating Characteristic ( ROC ) — scikit-learn 0.15.1 ROC curves are typically used in binary classification to study the output of a classifier. In order to extend ROC curve and ROC area to multi-class or multi- label ...
     5  +5 2014 jul 23support vector machines1.2. Support Vector Machines — scikit-learn 0.15.0 documentationThe support vector machines in scikit-learn support both dense (numpy.ndarray and convertible to that by numpy.asarray) and sparse (any scipy.sparse) sample  ...
     5  ~ 2014 jul 20handwritten in imagesRecognizing hand-written digits — scikit-learn 0.15.0 documentationRecognizing hand-written digits¶. An example showing how the scikit-learn can be used to recognize images of hand-written digits. This example is commented ...
     6  +3 2014 sep 14k meanssklearn.cluster. KMeans — scikit-learn 0.15.2 documentationNumber of time the k - means algorithm will be run with different centroid seeds. The final results will be the best output of n_init consecutive runs in terms of ...
     6  -4 2014 aug 04ridge parameter logistic regression1.1. Generalized Linear Models — scikit-learn 0.15.1 documentationRidge regression addresses some of the problems of Ordinary Least
     7  +1 2014 sep 28binary labelsklearn.preprocessing.LabelBinarizer — scikit-learn 0.15.2 At learning time, this simply consists in learning one regressor or binary classifier per class. In doing so, one needs to convert multi-class labels to binary labels  ...
     7  +5 2014 sep 27mean square errorsklearn.metrics.mean_squared_error — scikit-learn 0.15.2 sklearn.metrics.mean_squared_error¶. sklearn.metrics.mean_squared_error( y_true, y_pred, sample_weight=None)¶. Mean squared error regression loss ...
     7  -2 2014 sep 24mean shiftsklearn.cluster. MeanShift — scikit-learn 0.15.2 documentationMean shift clustering aims to discover “blobs” in a smooth density of samples. It is a centroid-based algorithm, which works by updating candidates for centroids ...
     7  +2 2014 sep 23tf idfsklearn.feature_extraction.text.TfidfVectorizer — scikit-learn 0.15.2 'numpy.int64'>, norm=u'l2', use_idf=True, smooth_idf=True, sublinear_tf=False) ¶. Convert a collection of raw documents to a matrix of TF - IDF features.
     7  -1 2014 sep 13tfidfsklearn.feature_extraction.text.TfidfTransformer — scikit-learn 0.15.2 Tf means term-frequency while tf-idf means term-frequency times inverse document-frequency. This is a common term weighting scheme in information retrieval, ...
     7  +10 2014 aug 30latent semantic indexing speed2.5. Decomposing signals in components (matrix factorization 2.5.2. Truncated singular value decomposition and latent semantic analysis ; 2.5. 3. .... The increased speed is reached by iterating over small chunks of the set of  ...
     7  +2 2014 aug 27learn to shufflesklearn.utils. shuffle — scikit- learn 0.15.1 documentationThis documentation is for scikit- learn version 0.15.1 — Other versions. If you use the software, ... Shuffle arrays or sparse matrices in a consistent way. This is a ...
     7  ~ 2014 aug 25the support vector machine1.2. Support Vector Machines — scikit-learn 0.15.1 documentation
     7  +52 2014 aug 15classify language from textWorking With Text Data — scikit-learn 0.15.1 documentationcd $TUTORIAL_HOME/data/ languages % less fetch_data.py % python ... of machine learning techniques, such as text classification and text clustering.
     8  +6 2014 sep 12installare releaseInstalling scikit-learn — scikit-learn 0.15.2 documentationInstall an official release . This is the best approach for users who want a stable version number and aren't concerned about running a slightly older version of ...
     8  -4 2014 aug 18hidden markov modelHidden Markov Models — scikit-learn 0.15.1 documentationThe sklearn. hmm module has now been deprecated due to it no longer matching the scope and the API of the project. It is scheduled for removal in the 0.17 ...
     8  -3 2014 aug 16set search parameters3.2. Grid Search : Searching for estimator parameters — scikit-learn Parameters that are not directly learnt within estimators can be set by searching a parameter space for the best Cross-validation: evaluating estimator ...
     9  ~ 2014 sep 23logistic regressionsklearn.linear_model. LogisticRegression — scikit-learn 0.15.2 This class implements L1 and L2 regularized logistic regression using the liblinear library. It can handle both dense and sparse input. Use C-ordered arrays or ...
     9  -1 2014 sep 06linear regressionsklearn.linear_model. LinearRegression — scikit-learn 0.15.1 coef_, array, shape (n_features, ) or (n_targets, n_features), Estimated coefficients for the linear regression problem. If multiple targets are passed during the fit (y ...
     9  -5 2014 aug 19hidden markov models
     9  ~ 2014 aug 02decision tree model1.8. Decision Trees — scikit-learn 0.15.1 documentationDecision Trees (DTs) are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the ...
     10  -2 2014 sep 21support vector machine1.2. Support Vector Machines — scikit-learn 0.15.2 documentation
     10  +11 2014 aug 31analyze semantic htmlSparse principal components analysis (SparsePCA and MiniBatchSparsePCA). 2.5.2. Truncated singular value decomposition and latent semantic analysis  ...
     11  ~ 2014 sep 03flow chartChoosing the right estimator — scikit-learn 0.15.1 documentationThe flowchart below is designed to give users a bit of a rough guide on how to approach ... Click on any estimator in the chart below to see it's documentation.
     11  +5 2014 aug 16k means clusteringsklearn. cluster . KMeans — scikit-learn 0.15.1 documentationThe number of clusters to form as well as the number of centroids to generate. max_iter : int, default: 300. Maximum number of iterations of the k - means  ...
     12  +22 2014 sep 30choose the rightChoosing the right estimator — scikit-learn 0.15.2 documentationChoosing the right estimator¶. Often the hardest part of solving a machine learning problem can be finding the right estimator for the job. Different estimators are ...
     12  -1 2014 sep 10n gradient1.3. Stochastic Gradient Descent — scikit-learn 0.15.2 documentationStochastic Gradient Descent (SGD) is a simple yet very efficient approach to ... SGD has been successfully applied to large-scale and sparse machine learning  ...
     12  +7 2014 sep 06mean of clustersklearn. cluster .KMeans — scikit-learn 0.15.1 documentationMaximum number of iterations of the k-means algorithm for a single run. ... 'k- means++' : selects initial cluster centers for k- mean clustering in a smart way to ...
     12  -6 2014 aug 03learn maximum loss methoda1.1. Generalized Linear Models — scikit- learn 0.15.1 documentationThe following are a set of methods intended for regression in which the target
     13  +45 2014 jul 19stock images pltPutting it all together — scikit-learn 0.15.0 documentationPipelining; Face recognition with eigenfaces; Open problem: Stock Market Structure
     14  +87 2014 sep 27troubleshooting of splitting machineMachine learning: the problem setting; Loading an example dataset ... in machine learning to evaluate an algorithm is to split the data at hand into two sets , one ...
     14  -1 2014 sep 16python sampling profilerHow to optimize for speed — scikit-learn 0.15.2 documentationFast matrix multiplications; Profiling Python code; Memory usage profiling ... The section A sample algorithmic trick: warm restarts for cross validation gives an ...
     14  +7 2014 sep 03manifold machine learning2.2. Manifold learning — scikit-learn 0.15.1 documentationManifold learning is an approach to non-linear dimensionality reduction. ..... G. Journal of Machine Learning Research (2008); “t-Distributed Stochastic Neighbor  ...
     14  +7 2014 aug 27linear discriminant analysissklearn. lda . LDA — scikit-learn 0.15.1 documentationLinear Discriminant Analysis ( LDA ). A classifier with a linear decision boundary, generated by fitting class conditional densities to the data and using Bayes' rule.
     14  +1 2014 aug 13working with textWorking With Text Data¶. The goal of this guide is to explore some of the main scikit-learn tools on a single practical task: analysing a collection of text ...
     14  +4 2014 aug 03logistic regression modelTo perform classification with generalized linear models , see Logistic regression . ... LinearRegression will take in its fit method arrays X, y and will store the ...
     14  +5 2014 jul 26bags of words4.1. Feature extraction — scikit-learn 0.15.0 documentationLimitations of the Bag of Words representation; 4.1.3.8. Vectorizing a large text corpus with the hashing trick; 4.1.3.9. Performing out-of-core scaling with ...
     15  +4 2014 sep 17image of lenaSegmenting the picture of Lena in regions — scikit-learn 0.15.2 Segmenting the picture of Lena in regions¶. This example uses Spectral clustering on a graph created from voxel-to-voxel difference on an image to break this ...
     15  -1 2014 aug 23create a decision tree
     15  +48 2014 aug 18order value variance4.2. Preprocessing data — scikit-learn 0.15.1 documentationImputation of missing values ; 4.2.7. ... If a feature has a variance that is orders of magnitude larger that others, ... Scaled data has zero mean and unit variance :.
     15  -11 2014 aug 17count text in htmlsklearn.feature_extraction. text .CountVectorizer — scikit-learn 0.15.1 'numpy.int64'>)¶. Convert a collection of text documents to a matrix of token counts . This implementation produces a sparse representation of the counts using ...
     15  ~ 2014 aug 11s v dsklearn.decomposition.TruncatedSVD — scikit-learn 0.15.1 In particular, truncated SVD works on term count/tf-idf matrices as returned by the vectorizers in sklearn.feature_extraction.text. In that context, it is known as ...
     15  +10 2014 aug 11the decision tree
     16  +6 2014 sep 18information gain time compley1.8. Decision Trees — scikit-learn 0.15.2 documentationThe deeper the tree, the more complex the decision rules and the fitter the model.
     16  -2 2014 sep 14learn to countsklearn.feature_extraction.text.CountVectorizer — scikit- learn 0.15.2 This documentation is for scikit- learn version 0.15.2 — Other versions. If you use the software ... Convert a collection of text documents to a matrix of token counts .
     16  +4 2014 sep 13sparse codingsklearn.decomposition.sparse_encode — scikit-learn 0.15.1 Each row of the result is the solution to a sparse coding problem. The goal ... The dictionary matrix against which to solve the sparse coding of the data. Some of ...
     16  +85 2014 sep 01in a grid3.2. Grid Search: Searching for estimator parameters — scikit-learn Exhaustive Grid Search. 3.2.1.1. Scoring functions for parameter search. 3.2.2. Randomized Parameter Optimization; 3.2.3. Alternatives to brute force parameter  ...
     16  +77 2014 aug 24linux python module soInstalling scikit-learn — scikit-learn 0.15.1 documentationAt this time scikit-learn does not provide official binary packages for Linux so ... packages uses distutils, which is the default way of installing python modules .
     16  +8 2014 aug 09print mashine vectorSupervised learning: predicting an output variable from high In the scikit-learn for classification tasks, y is a vector of integers. Note: See the Introduction to machine learning with Scikit-learn Tutorial for a quick run-through .... print (regr.coef_) [ 0.30349955 -237.63931533 510.53060544 327.73698041 ...
     16  -4 2014 jul 27novelty and learning4.6. Novelty and Outlier Detection — scikit- learn 0.13.1 documentationThe scikit- learn project provides a set of machine learning tools that can be used both for novelty or outliers detection. This strategy is implemented with objects ...
     17  +7 2014 sep 13lena imageA demo of structured Ward hierarchical clustering on Lena image A demo of structured Ward hierarchical clustering on Lena image ¶. Compute the segmentation of a 2D image with Ward hierarchical clustering. The clustering is ...
     17  -2 2014 aug 27machine learning open sourceMachine Learning in Python ... and reusable in various contexts; Built on NumPy, SciPy, and matplotlib; Open source , commercially usable - BSD license.
     17  +25 2014 aug 07learn basic htmlAn introduction to machine learning with scikit- learn — scikit- learn Section contents. In this section, we introduce the machine learning vocabulary that we use through-out scikit- learn and give a simple learning example.
     17  +9 2014 aug 04machin warning label vectorIf the prediction task is to classify the observations in a set of finite labels , in other words to
     17  +2 2014 aug 02open source machine learningscikit-learn: machine learning in Python — scikit-learn 0.15.0
     17  -1 2014 jul 26what is decision tree1.8. Decision Trees — scikit-learn 0.15.0 documentation
     17  -2 2014 jul 18install python ubuntuInstalling scikit-learn — scikit-learn 0.15.0 documentationInstall the version of scikit-learn provided by your operating system or Python ... systems, which include Ubuntu , you can install all these requirements by issuing:.
     17  -9 2014 jul 17learn as one1.10. Multiclass and multilabel algorithms — scikit- learn 0.15.0 Below is a summary of the classifiers supported by scikit- learn grouped by strategy; you don't need the meta-estimators in this class if you're using one of these ...
     18  -3 2014 oct 02python data miningscikit-learn. Machine Learning in Python . Simple and efficient tools for data mining and data analysis; Accessible to everybody, and reusable in various contexts ...
     18  +18 2014 sep 20pca آنالیزPrincipal component analysis ( PCA ). 2.5.1.1. Exact PCA and probabilistic interpretation; 2.5.1.2. Approximate PCA ; 2.5.1.3. Kernel PCA ; 2.5.1.4. Sparse principal ...
     18  +8 2014 sep 19svm call optionssklearn. svm .SVC — scikit-learn 0.15.2 documentationThis must be enabled prior to calling fit , and will slow down that method. ... See the section about multi-class classification in the SVM section of the User Guide for details. ... set_params(**params), Set the parameters of this estimator.
     18  +16 2014 sep 01what is logistic regeresionThe following are a set of methods intended for regression in which the ... To perform classification with generalized linear models, see Logistic regression .
     18  +16 2014 aug 21sentiment analysis tutorialExercise 1: Language identification; Exercise 2: Sentiment Analysis on movie ... To get started with this tutorial , you firstly must have the scikit-learn and all of its ...
     18  -3 2014 jul 25brute force traing1.4. Nearest Neighbors — scikit-learn 0.15.0 documentationBecause the query set matches the training set, the nearest neighbor of each point is .... The most naive neighbor search implementation involves the brute - force  ...
     19  +68 2014 sep 24модели wmcsklearn.mixture.GMM — scikit-learn 0.15.2 documentationRepresentation of a Gaussian mixture model probability distribution. This class ... n_components=2, n_init=1, n_iter=100, params=' wmc ', random_state=None, ...
     19  -2 2014 sep 07centroid in different with in1.4. Nearest Neighbors — scikit-learn 0.15.1 documentationNearest Centroid Classifier. 1.4.5.1. Nearest Shrunken Centroid ... It acts as a uniform interface to three different nearest neighbors algorithms: BallTree, KDTree, ...
     19  ~ 2014 aug 19learn how to skiscikit- learn : machine learning in Python — scikit- learn 0.15.1 scikit- learn . Machine Learning in Python. Simple and efficient tools for data mining and data analysis; Accessible to everybody, and reusable in various contexts ...
     20  +81 2014 sep 29python pippip install -U scikit-learn. If there are no binary packages matching your Python version you might to try to install scikit-learn and its dependencies from Christoph  ...
     20  -4 2014 sep 11outliers2.7. Novelty and Outlier Detection — scikit-learn 0.15.2 documentationThe scikit-learn project provides a set of machine learning tools that can be used both for novelty or outliers detection. This strategy is implemented with objects ...
     20  -4 2014 sep 06image shapes extractor4.1. Feature extraction — scikit-learn 0.15.1 documentationImage feature extraction ... Connectivity graph of an image . « ...... Similarly, grid_to_graph build a connectivity matrix for images given the shape of these image .
     20  +16 2014 aug 27metric conversion vector4.5. Pairwise metrics , Affinities and Kernels — scikit-learn 0.15.1 There are a number of ways to convert between a distance metric and a ... cosine similarity, because Euclidean (L2) normalization projects the vectors onto the ...
     20  +17 2014 aug 03data mining python
     21  +44 2014 sep 19what does metoos mean2.2. Manifold learning — scikit-learn 0.15.2 documentationI mean the bare necessities. Old Mother Nature's .... The second term has to do with constructing the weight matrix from multiple weights. In practice, the added ...
     21  +6 2014 sep 13naive1.7. Naive Bayes — scikit-learn 0.15.2 documentationNaive Bayes methods are a set of supervised learning algorithms based on applying Bayes' theorem with the “ naive ” assumption of independence between ...
     21  +20 2014 jul 24python open websiteMachine Learning in Python ... and reusable in various contexts; Built on NumPy, SciPy, and matplotlib; Open source, commercially usable - BSD license.
     22  -4 2014 aug 14area under the curvesklearn.metrics.roc_auc_score — scikit-learn 0.15.1 documentationsklearn.metrics.roc_auc_score(y_true, y_score, average='macro', sample_weight =None)¶. Compute Area Under the Curve (AUC) from prediction scores.
     22  +4 2014 aug 05run python on ubantoInstall the version of scikit-learn provided by your operating system or Python
     22  -5 2014 jul 16learning to skiscikit- learn : machine learning in Python — scikit- learn 0.15.0
     23  +4 2014 sep 28learning pythonscikit- learn : machine learning in Python — scikit- learn 0.15.2 scikit- learn . Machine Learning in Python . Simple and efficient tools for data mining and data analysis; Accessible to everybody, and reusable in various contexts ...
     23  +13 2014 sep 22user contentsUser guide: contents — scikit-learn 0.15.2 documentationThis documentation is for scikit-learn version 0.15.2 — Other versions. If you use the software, please consider citing scikit-learn. « 1. Supervised learning · 1.1.
     23  +10 2014 sep 16install easy install pythonInstall the version of scikit-learn provided by your operating system or Python ... sudo apt-get install build-essential python -dev python - setuptools \ python -numpy  ...
     23  -7 2014 sep 06lassosklearn.linear_model. Lasso — scikit-learn 0.15.1 documentationLasso (alpha=1.0, fit_intercept=True, normalize=False, precompute='auto', copy_X=True, max_iter=1000, tol=0.0001, warm_start=False, positive=False)¶.
     23  -6 2014 aug 28decision tree example
     23  -3 2014 aug 14ubuntu windows installerDebian and derivatives ( Ubuntu ); Python(x,y) for Windows ; Canopy and ... Under Debian-based operating systems, which include Ubuntu , you can install all ...
     24  -13 2014 aug 25example of decision tree
     24  +1 2014 aug 24area under a curvesklearn.metrics.average_precision_score — scikit-learn 0.15.1 This score corresponds to the area under the precision-recall curve . Note: this implementation is restricted to the binary classification task or multilabel ...
     24  ~ 2014 jul 29decision tree examplesFor instance, in the example below, decision trees learn from data to approximate a sine curve with a set of if-then-else decision rules. The deeper the tree , the ...
     25  +7 2014 sep 11debian windows installerDebian and derivatives (Ubuntu); Python(x,y) for Windows ; Canopy and Anaconda ... Under Debian -based operating systems, which include Ubuntu, if you have ...
     25  +12 2014 aug 19python video tutorialExternal Resources, Videos and Talks — scikit-learn 0.15.1 For written tutorials , see the Tutorial section of the documentation. ... For those that are still new to the scientific Python ecosystem, we highly recommend the ...
     25  +15 2014 aug 02clasification of software metricsklearn. metrics . classification_report — scikit-learn 0.15.0 If you use the software , please consider citing scikit-learn. sklearn. metrics . classification_report ... Build a text report showing the main classification metrics  ...
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