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The shape function is a function in Numpy.core.fromnumeric, whose function is to read the length of the matrix, for example, Shape[0] is to read the length of the first dimension of the matrix. Its input parameters can make an integer representation of a dimension, or it can be a matrix.Use Shape to import numpyThe tile function is in the Python module numpy.lib.shape_base, and his function is to repeat an array. For example, Tile (a,n), function is to repeat the array a n times to form a new ar

=grid_search.best_estimator_.get_ params () for param_name in sorted (Parameters.keys ()): print (' \t%s:%r '% (Param_name,best_parameters[param_name]) )Output Result:Best results: 0.929 optimal parameters: clf__max_depth:250 clf__min_samples_leaf:1 clf__min_samples_split:3 clf__n_estimators:50Predictions=grid_search.predict (x_test) print Classification_report (y_test,predictions)Output Result:Precision Recall F1-score Support0 0.98 1.00) 0.99 7051 0.97 0.90) 0.93 115Avg/total 0.98 0.98 0.98

products, and so on, can be abstracted into vectors to allow the computer to know the distance between two properties. For example: We believe that 18-year-olds are closer to the 24-year-old than the 12-year-old, which is closer to the product than the computer, and so on.as long as the real-world objects can be abstracted into vectors, you can use the K-means algorithm to classify .In the "K-mean Clustering (K-means)" This article cited a very good application example, the author made a vector

nodes on the node on behalf of a variety of fractions, example to get the classification result of Class 1The same input is transferred to different nodes and the results are different because the respective nodes have different weights and biasThis is forward propagation.10. MarkovVideoMarkov Chains is made up of state and transitionsChestnuts, according to the phrase ' The quick brown fox jumps over the lazy dog ', to get Markov chainStep, set each word to a state, and then calculate the prob

train our models. Let's see what methods are available and what parameters are required as input. First we import the built-in library file als:import org.apache.spark.mllib.recommendation.ALSThe next operation is done in Spark-shell. Under Console, enter ALS. (Note that there is a point behind the ALS) plus the TAP key:The method we are going to use is the train method.If we enter Als.train, we will return an error, but we can look at the details of this method from this error:As you can see,

-validation approach. Cross-validation A simple idea to solve the above model selection problem is that I use 70% of the data to train each model, with 30% of the data for training error calculation, and then we compare the training errors of each model, we can choose the training error is relatively small model. If you do not refer to these errors (learn the theory of experience risk minimization--andrew ng machine

This is according to the (Shanghaitech University) Wang Hao's teaching of the finishing.Required pre-Knowledge: score, higher garbage, statistics, optimizationMachine learning: (Tom M. Mitchell) "A computer program was said to learn from experience E with respect to some CL The performance of the tasks T and measure p if its performance at the tasks in T, as measured by P, IM proves with experience E ".? What is experience:historical data? How to lear

Transferred from: http://www.csdn.net/article/2015-10-16/2825925First of all, let me start with my intentions . Machine learning system now much more red NB this thing I don't have to repeat. But because of the particularity of machine learning system, it is not easy to build a reliable and useful system. Every time I

First, MATLAB computer visioncontourlets-MATLAB source code for Contour Wave transformation and its use functionshearlets-MATLAB source code for Shear Wave transformationcurvelets-curvelet transformation of MATLAB source code (Curvelet transformation is to the higher dimension of the wavelet transform to the promotion of the different scales to represent the image)bandlets-bandlets transformation of MATLAB source codeNatural language ProcessingNLP-A NLP library of MATLABGeneral

Machine learningMachine Learning (machine learning, ML) is a multidisciplinary interdisciplinary, involving many disciplines such as probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and so on. Specialized in computer simulation or realization of human

This article is reproduced from: http://www.csdn.net/article/2015-10-01/2825840 Absrtact: Deep learning based on Hadoop is an innovative method of deep learning. The deep learning based on Hadoop can not only achieve the effect of the dedicated cluster, but also has a unique advantage in enhancing the Hadoop cluster, distributed depth

Learning Guide for machine learning beginners (experience sharing)2013-09-21 14:47I computer research two, the professional direction of natural language processing, individuals interested in machine learning, so began to learn. So, this guy is a rookie ... It is because of

After 2 months of knowledge of machine learning. I've found that machine learning has a variety of directions. Page sort. Speech recognition, image recognition, recommender system, etc. Algorithms are also varied. After seeing the other books, I found that except for the K-mean clustering. Bayesian, neural network, onl

This paper mainly records the cost function of neural network, the usage of gradient descent in neural network, the reverse propagation, the gradient test, the stochastic initialization and other theories, and attaches the MATLAB code and comments of the relevant parts of the course work. Concepts of neural networks, models, and calculation of predictive classification using forward propagation refer to Andrew Ng Machine

Project applicability analysis of main machine learning algorithmsSome time ago Alphago with the Li Shishi of the war and related deep study of the news brush over and over the circle of friends. Just this thing, but also in the depth of machine learning to further expand, and the breadth of

Brief introductionBefore I introduce machine learning, I would like to start by listing some examples of machine learning: junk e-mail detection: Identifies what is spam and what is not, based on the messages in the mailbox. Such a model can help categorize spam and non-spam messages by programs. This example

Reprint Please specify source: http://www.cnblogs.com/ymingjingr/p/4271742.htmlDirectory machine Learning Cornerstone Note When you can use machine learning (1) Machine learning Cornerstone Note 2--When you can use

This article is a translation of the article, but I did not translate the word by word, but some limitations, and added some of their own additions.Machine Learning (machines learning, ML) is what, as a mler, is often difficult to explain to everyone what is ML. Over time, it is found to understand or explain what machine lea