data mining fourth edition practical machine learning tools and techniques

of the current node is the middle half of the distance of all its leaf nodes is float (NUMLEAFS)/2.0/plottree.totalw* 1, but since the start Plottree.xoff assignment is not starting from 0, but the left half of the table, so also need to add half the table distance is 1/2/plottree.totalw*1, then add up is (1.0 + float (numleafs))/2.0/ Plottree.totalw*1, so the offset is determined, then the X position becomes Plottree.xoff + (1.0 + float (numleafs))/2.0/PLOTTREE.TOTALW3, for Plottree function p

First, the visualization method Bar chart Pie chart Box-line Diagram (box chart) Bubble chart Histogram Kernel density estimation (KDE) diagram Line Surface Chart Network Diagram Scatter chart Tree Chart Violin chart Square Chart Three-dimensional diagram Second, interactive tools Ipython, Ipython Notebook plotly Iii. Python IDE Type Pycharm, specifying a Java swi

(written in front) said yesterday to write a machine learning book, then write one today. This book is mainly used for beginners, very basic, suitable for sophomore, junior to see the children, of course, if you are a senior or a senior senior not seen machine learning is also applicable. Whether it's studying intellig

What is http://www.quora.com/What-is-data-science data science?Http://www.quora.com/How-do-I-become-a-data-scientist how can I become a data scientist?Http://www.quora.com/Data-Science/How-does-data-science-differ-from-traditional

Read "Data Mining Technology (third edition)"-Thoughts on marketing, sales and customer relationship management This book is not a purely data mining theory book, you can probably guess from the subtitle of this book. For a layman like me in the field of

, simulated annealing algorithm), GA (Genetic algorithm genetic algorithm)Feature Selection (Feature selection algorithm):Mutual information (Mutual information), Documentfrequence (document frequency), information Gain (information gain), chi-squared test (Chi-square test), Gini (Gini coefficient).Outlier Detection (anomaly detection algorithm):Statistic-based (based on statistics), distance-based (distance based), density-based (based on density), clustering-based (based on clustering).

the VC dimension theory, we need more data to get the same generalization ability.For the second case, there is the same reason. We also inadvertently enlarged the size of the hypothesis set.can refer to Raymond Paul Mapa generalization theory (lesson six)There are two ways to resolve this:1, avoid data snooping. -_-2, can not avoid in the calculation of generalization theory when the

algorithm)Feature Selection (Feature selection algorithm):Mutual information (Mutual information), Documentfrequence (document frequency), information Gain (information gain), chi-squared test (Chi-square test), Gini (Gini coefficient).Outlier Detection (anomaly detection algorithm):Statistic-based (based on statistics), distance-based (distance based), density-based (based on density), clustering-based (based on clustering).Learning to Rank (based o

)Feature Selection (Feature selection algorithm):Mutual information (Mutual information), Documentfrequence (document frequency), information Gain (information gain), chi-squared test (Chi-square test), Gini (Gini coefficient).Outlier Detection (anomaly detection algorithm):Statistic-based (based on statistics), distance-based (distance based), density-based (based on density), clustering-based (based on clustering).Learning to Rank (based on

algorithm), GA (Genetic algorithm genetic algorithm)Feature Selection (Feature selection algorithm):Mutual information (Mutual information), Documentfrequence (document frequency), information Gain (information gain), chi-squared test (Chi-square test), Gini (Gini coefficient).Outlier Detection (anomaly detection algorithm):Statistic-based (based on statistics), distance-based (distance based), density-based (based on density), clustering-based (based on clustering).

Summary:Orange Orange is a component-based data mining and machine learning software suite that features a friendly, yet powerful, fast and versatile visual programming front end for browsing data analysis and visualization, and the base binds Python for scripting developmen

specific job requirements, image algorithm For example, now deep learning hot not I said, so the basic convolution neural network algorithm , image classification , image detection The more famous paper in recent years should read it. If you have a condition, use it like a caffe,tensorflow frame.2. Machine Learning EngineerThis post is basically the same as the

/uv Analysis (Skip) ...Finally find a friend circle to share and collect the hourly data graphThe results found that the friend circle limit flow, basically share the number of times a 15,000 is dry down. After July 14, it is completely limited to the peak of the current level.Through the above analysis, we find that the bottleneck of our system is the limit flow of the circle of friends. Solution business negotiation, or multi-domain. Is there any ot