Add to ORKGGrouping can use clustering to group data based on the similarity between the data, so that the data with the closest resemblance is in one cluster while the different data is in another group. The X-Means algorithm is the development of K-Means. The weakness of X-Means is that in determining the distance matrix, the distance matrix is an important factor that depends on the X-Means algorithm data set. The resulting distance matrix value will affect the performance of the algorithm. The results of the study are: testing with variations in the number of centroids (K) with values of 2,3,4,5,6,7,8,9,10. The author concludes that the number of centroids 3 and 4 has a better iteration value compared to the number of centroids that are gettin...
Clustering is a useful technique that organizes a large quantity of unordered datasets into a small ...
Teknik Clustering merupakan salah satu metode Data Mining yang bersifat tanpa arahan (unsupervised l...
K-means is one of the simplest unsupervised learning algorithms that solve the well known clustering...
Grouping can use clustering to group data based on the similarity between the data, so that the data...
The K-Means Clustering algorithm is commonly used by researchers in grouping data. The main problem ...
Clustering is a technique in data mining that groups a set of data into groups (clusters) of similar...
Heuristic data requires appropriate clustering methods to avoid casting doubt on the information gen...
In data mining, there are several algorithms that are often used in grouping data, including K-Means...
huge data is a big challenge. Clustering technique is able to find hidden patterns and to extract us...
Clustering is an unsupervised classification method with major aim of partitioning, where objects i...
Advances in recent techniques for scientific data collection in the era of big data allow for the sy...
K-medoids clustering uses distance measurement to find and classify data that have similarities and ...
Cluster analysis method is one of the most analytical methods of data mining. The method will direct...
Perkembangan teknologi mengakibatkan ketersediaan data yang semakin meningkat, peningkatan jumlah da...
Working with huge amount of data and learning from it by extracting useful information is one of the...
Clustering is a useful technique that organizes a large quantity of unordered datasets into a small ...
Teknik Clustering merupakan salah satu metode Data Mining yang bersifat tanpa arahan (unsupervised l...
K-means is one of the simplest unsupervised learning algorithms that solve the well known clustering...
Grouping can use clustering to group data based on the similarity between the data, so that the data...
The K-Means Clustering algorithm is commonly used by researchers in grouping data. The main problem ...
Clustering is a technique in data mining that groups a set of data into groups (clusters) of similar...
Heuristic data requires appropriate clustering methods to avoid casting doubt on the information gen...
In data mining, there are several algorithms that are often used in grouping data, including K-Means...
huge data is a big challenge. Clustering technique is able to find hidden patterns and to extract us...
Clustering is an unsupervised classification method with major aim of partitioning, where objects i...
Advances in recent techniques for scientific data collection in the era of big data allow for the sy...
K-medoids clustering uses distance measurement to find and classify data that have similarities and ...
Cluster analysis method is one of the most analytical methods of data mining. The method will direct...
Perkembangan teknologi mengakibatkan ketersediaan data yang semakin meningkat, peningkatan jumlah da...
Working with huge amount of data and learning from it by extracting useful information is one of the...
Clustering is a useful technique that organizes a large quantity of unordered datasets into a small ...
Teknik Clustering merupakan salah satu metode Data Mining yang bersifat tanpa arahan (unsupervised l...
K-means is one of the simplest unsupervised learning algorithms that solve the well known clustering...