What is Bori CE?

The Bhandarkar Institute of Oriental Research (BORI), Pune undertook the Mahabharata project way back in 1930s. They referred to 1261 or some such Sanskrit versions. By carefully comparing all versions, the scholars came up with what was known as the Critical Edition CE. The BORI CE was published circa 1961.

What is the full form of Bori?

The Bhandarkar Oriental Research Institute (BORI) is located in Pune, Maharashtra, India. It was founded on 6 July 1917 and named after Ramakrishna Gopal Bhandarkar (1837–1925), long regarded as the founder of Indology (Orientalism) in India.

What is a Critical Edition of a book?

A scholarly edition that does not replicate the text of one document, but rather presents a corrected text, compiled from one or more source documents, and an apparatus recording editorial …

Who first translated Ramayana into English?

Ralph T. H. Griffith
It was Ralph T. H. Griffith, who wrote the first complete English translation of the Ramayana.

Who is the first Indian to translate the Mahabharata into English?

Kisari Mohan Ganguli
Vyasa lived around the 3rd millennium BCE. Kisari Mohan Ganguli (also K. M. Ganguly) was an Indian translator, who is most known for the first complete English translation of the Sanskrit epic Mahabharata published as The Mahabharata of Krishna-Dwaipayana Vyasa Translated into English Prose between 1883 to 1896.

What is the difference between Boyer Moore algorithm and KMP algorithm?

KMP Algorithm scans the given string in the forward direction for the pattern, whereas Boyer Moore Algorithm scans it in the backward direction.

What is convergence in k-means clustering?

Convergence refers to the condition where the previous value of centroids is equal to the updated value. In the case of finding initial centroids using Lloyd’s algorithm for K-Means clustering, we were using randomization.

What is the difference between k-means and k-medoids clustering?

The algorithm of K-Medoids clustering is called Partitioning Around Medoids (PAM) which is almost the same as that of Lloyd’s algorithm with a slight change in the update step. Update centroids: In the case of K-Means we were computing mean of all points present in the cluster. But for the PAM algorithm updation of the centroid is different.

What is the problem of initialization sensitivity in k-means clustering?

In the case of finding initial centroids using Lloyd’s algorithm for K-Means clustering, we were using randomization. The initial k-centroids were picked randomly from the data points. This randomization of picking k-centroids points results in the problem of initialization sensitivity.