## How to learn Programming?

Credits: Think360 Studios There are many websites, books, and other resources that teach us programming but not all of them tell us that how to learn programming and moreover how to get consistency in this learning period. That’s exactly what, we are going to cover today.   Set Your  Goal : Credits: Northbound Sales Training   First of all, you need a goal, for what you want to learn programming otherwise if you will start learning t...

## Android : The Flexible Operating System

Android is leading the smartphone market as a champion with the leadership rate of 84 %, over 3.3 billion smartphones are running on the Android operating system because of its efficiency and performance.   Android : It is an open source operating system which is made on Linux-kernel. Today Android is featured in almost 70% of smart electronics globally but the primary sector that has hooked with this operating system is the smartphone ma...

## Introduction of Decision Trees

Decision Tree:Overview in different kinds of supervised data mining techniques the Decision Tree are one of the most popular classification and prediction technique. basically the training data samples are organized in form of tree data structure. where the nodes of tree shows the attributes of the data set and edges can be used for demonstrating the values of these attributes. additionally the leaf node of the tree contains the decisions of t...

Black-hole Attack in MANET
/ August 17, 2017

Mobile Ad-hoc Network(MANET) Attack Wireless networks can be basically either infrastructure based networks or infrastructure less networks. The infrastructure based networks uses fixed base stations, which are responsible for coordinating communication between the mobile hosts (nodes). The ad hoc networks falls under the class of infrastructure less networks, where the mobile nodes communicate with each other without any fixed infra...

Decision Trees Applications
/ August 14, 2017

Decision Tree Overview In data mining techniques two kinds of basic learning processes are available namely supervised and unsupervised. when we talk about the supervised learning techniques the decision tree learning is one of the most essential technique of classification and prediction. A number of different kinds of decision tree algorithms are available i.e. ID3, C4.5, C5.0, CART, SLIQ and others. All these algorithms the used t...

ID3 Decision Tree in Data Mining
/ August 11, 2017

ID3 Decision Tree Overview Engineered by Ross Quinlan the ID3 is a straightforward decision tree learning algorithm. The main concept of this algorithm is construction of the decision tree through implementing a top-down, greedy search by the provided sets for testing every attribute at each node of decision. With the aim of selecting the attribute which is most useful to classify a provided set of data, a metric is introduced named ...

k Nearest Neighbor (KNN)
/ August 11, 2017

k Nearest Neighbor (KNN): introduction The necessity of data mining techniques has emerged quite immensely nowadays due to massive increase in data. Data mining is the process of extracting patterns and mining knowledge from data. K nearest neighbors is a simple algorithm that stores all available cases and classifies new cases based on a similarity measure (e.g., distance functions). KNN has been used in statistical estimation and p...

Introduction of Decision Trees
/ August 11, 2017

Decision Tree:Overview in different kinds of supervised data mining techniques the Decision Tree are one of the most popular classification and prediction technique. basically the training data samples are organized in form of tree data structure. where the nodes of tree shows the attributes of the data set and edges can be used for demonstrating the values of these attributes. additionally the leaf node of the tree contains the deci...

Web recommendation system
/ August 11, 2017

Web recommendation system: Introduction The term recommendation is used for describing the suggestions of a particular product or service. therefore the web recommendation systems are a essential part of e-commerce applications. The users who search about some kinds of product or services the recommendation systems helps them by suggesting the most appropriate product or services. In most of the cases the web based recommendation sys...

Fuzzy C means
/ August 11, 2017

Fuzzy C-means: Overview the fuzzy c-means algorithm is one of the most popular clustering technique in data mining. that technique enable the data objects to be available in more than one cluster at the time. therefore that technique can be used for other clustering technique implementations. that is also a unsupervised technique of data mining. that technique directly input the data samples as input and produces the clusters of data...

K-Means Algorithm with Numerical Explanation
/ August 10, 2017

K-means clustering Overview in a number of classical data mining techniques the k-means algorithm is one of the most popular technique of unsupervised learning or clustering. that technique can be used with any kind of mining techniques web mining, text mining or any structured data mining. that algorithm is suitable to used for partitioning of data into K number of clusters. therefore that technique is also known as partition based ...

Classification and prediction in data mining
/ August 10, 2017

Classification is a technique of supervised learning in data mining. that technique is applied when the data patterns or samples are having some predefined pattern labels or class labels. the supervised learning algorithms first prepare the data models based on the existing patterns. these existing patterns are known as training samples. additionally the preparation of data models are known as the training of algorithms. after the tr...

Clustering in Data mining
/ August 10, 2017

clustering is a technique to prepare the group of similar data objects based on their internal similarity. the data objects are representing the properties or features of an individual pattern of data. these properties or features are used for computing the similarity or differences among the data objects. the data objects which are grouped is termed as the cluster of data. the cluster analysis includes two main components first is k...

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