原创 機器學習中Training, Validation 和 Test 集合之間的區別
Mostly, we divide the whole set into 3 parts. 1. Training Set Train your model. You can optimize your model, chan
原创 [Mahout in action]--Recommender System
Mahout User-based Recommender’s Component Interaction The Refresh of Mahout User-based component! The arrow of
原创 Installing maven 3.3.3 on Ubuntu
sudo apt-get purge -y maven wget http://apache.cs.utah.edu/maven/maven-3/3.3.3/binaries/apache-maven-3.3.3-bin.tar.
原创 [Java]--Keyword super
1. Acessing Superclass Members If we have Override certain superclass’ method. Perhaps we could invoke the overrid
原创 [Machine Learning_Andrew Ng]--Sigmoid() Function.
g(z)=11+e−z In octave function g = sigmoid(z) %SIGMOID Compute sigmoid functoon % J = SIGMOID(z) computes the sig
原创 [LeetCode]--131. Palindrome Partitioning(backTracking && DFS && DP)
1. Problem Given a string s, partition s such that every substring of the partition is a palindrome. Return all pos
原创 [LeetCode]--242. Valid Anagram(Count table && char array sort())
1. Program Problem Link: https://leetcode.com/problems/valid-anagram/ 2. Solution 2.1. Count Table Solution publi
原创 [Java]--Singleton vs Static
Singleton Key Point: 1. Only one instance for the singleton type class. 2. All values stored in the singleton wi
原创 [Java]--Java static keyword – Class, Method, Variable, Block, import
The Link:http://www.journaldev.com/1365/java-static-keyword-class-method-variable-block-import 1. Java static vari
原创 [Java]--final key word
To be simple, items declared with the final word can not be changed. final class: can not be extended by any subcl
原创 Hyperparameters in Machine Learning
In machine learning, we use the term hyperparameter to distinguish from standard model parameters. So, it is worth
原创 [Machine_Learning]--Backpropagation
這裏只提供一些關於反向傳播(Backpropagation)鏈接資源, this is part of the neural network. And neural network is basis of deep learnin
原创 Access Modifier(Private & Protected & Public)
http://stackoverflow.com/questions/215497/in-java-difference-between-default-public-protected-and-private
原创 [Mahout in Action] Representating Recommender Data
In-memory representations without preference values GenericBooleanPrefDataModel , which is similar with GenericData
原创 [Machine Learning]---ROC(Receiver Operating Characteristic) Curve
1. Some Basic Concepts True Positive Rate: TPR=TPTP+FN False Positive Rate FPR=FPFP+TN 2. ROC Curve ROC use the