Knowing an algorithm and using an algorithm are two different things.
What should I do if I find that the model has a big error after you train the data?
1) Obtain more data. It may be useful.
2) reduce feature dimensions. You can manually select one or use mathematical methods such as PCA.
3) Obtain more features. Of course, this method is time-consuming and not necessarily useful.
4) add polynomial features. Are you trying to save your life?
5) Build your own, new, and better features. A litt
Machine Learning 4, machine learning
Probability-based classification method: Naive BayesBayesian decision theory
Naive Bayes is a part of Bayesian decision-making theory. Therefore, before explaining Naive Bayes, let's take a quick look at Bayesian decision-making theory knowledge.
The core idea of Bayesian decision-m
In machine learning, often need to calculate the distance between each sample, used for classification, according to distance, different samples grouped into a class; But in the current machine learning algorithm, the distance calculation mode is endless, then this blog is mainly to comb the current
A brief introduction to Learning _note1 against Sample machine
Machine learning methods, such as SVM, neural network, etc., although in the problem such as image classification has been outperform the ability of human beings to deal with similar problems, but also has its inherent defects, that our training sets are fe
The Ames Razor principle (Occam ' s Razor)One sentence is said, "an explanation of the data should is mad as simple as possible,but no simpler".The meaning of machine learning is that the simplest explanation of the data is the best explanation (the simplest model, fits the data is also and the most plausible).For example, the picture above, the right is not better than the left to explain? That's obviously
July online April machine learning algorithm class notes--no.1
Objective
Machine learning is a multidisciplinary interdisciplinary, including probability theory, statistics, convex analysis, feature engineering and so on. Recently followed the July algorithm to learn the knowledge of
Machine learning practices in python3.x and python machine learning practices
Machine Learning Practice this book is written in the python2.x environment, while many functions and 2 in python3.x. the names or usage methods in x ar
findF1scoreThe algorithm with the largest value. 5. Data for Machine Learning (
Machine Learning data
)
In machine learning, many methods can be used to predict the problem. Generally, when the data size increases, the accura
A probe into machine learning1. What is machine learningLearning refers to the skill that a person refines in the course of observing things, rather than learning, machine learning refers to the ability of a computer to gain some experience (i.e. a mathematical model) in a p
Machine learning system Design (Building machines learning Systems with Python)-Willi Richert Luis Pedro Coelho General statementThe book is 2014, after reading only found that there is a second version of the update, 2016. Recommended to read the latest version, the ability to read English version of the proposal, Chinese translation in some places more awkward
Core ML machine learning, coreml Machine Learning
At the WWDC 2017 Developer Conference, Apple announced a series of new machine learning APIs for developers, including visual APIs for facial recognition and natural language proce
Microsoft Azure cloud service introduces the machine learning module. Users only need to upload data and use some algorithm interfaces and R or other language interfaces provided by the machine learning module, you can use Microsoft Azure's powerful cloud computing capabilities to implement your
The essential difference between classification and clustering in machine learning
There are two kinds of big problems in machine learning, one is classification, the other is clustering.In our life, we often do not have too much to distinguish between these two concepts, think clustering is classification, classificat
1. Decision Tree applicable conditions: The data of different class boundary is non-linear, and by continuously dividing the feature space into a matrix to simulate. There is a certain correlation between features. The number of feature values should be similar, because the information gain is biased towards more numerical characteristics. Advantages: 1. Intuitive decision-making rules; 2. Nonlinear characteristics can be handled; 3. The interaction between variables is considered. Disadvanta
Use Python to master machine learning in four steps and python to master machines in four steps
To understand and apply machine learning technology, you need to learn Python or R. Both are programming languages similar to C, Java, and PHP. However, since Python and R are both relatively young and "Far Away" from the CP
Customer Churn
"Loss rate" is a business term that describes the customer's departure or stop payment of a product or service rate. This is a key figure in many organizations, as it is usually more expensive to get new customers than to retain the existing costs (in some cases, 5 to 20 times times the cost).
Therefore, it is invaluable to understand that it is valuable to maintain customer engagement because it is a reasonable basis for developing retention policies and implementing operational
1. What is machine learningMachine learning is the conversion of unordered data into useful information.The main task of machine learning is to classify and another task is to return.Supervised learning: It is called supervised learning
Python Machine Learning Theory and Practice (5) Support Vector Machine and python Learning Theory
Support vector machine-SVM must be familiar with machine learning, Because SVM has alwa
http://sourceforge.net/projects/numpy/files/download the corresponding version of the NumPy, everywhere, find a not python2.7Use Pip, please.Pip Install NumPyDownload finished, the hint does not install C + +, meaning is also to install VS2008, but installed is VS2012, had to download a VC for Pythonhttp://www.microsoft.com/en-us/download/confirmation.aspx?id=44266Re-pip, wait for the most of the day, the final count is successfulInput command introduced NumPyFrom numpy Import *Operation:InputRa
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