I have a variable number of points (not more than 10) - which are probability values. Amongst these points some of them refer to the peaks on the curve if the points are fit on a curve. I want to find the points that represent the peaks on the curve. Is there a simple way to find the peaks? Do I need to do any curve fitting first to spot the peaks?
The problem is to find the split points in a word (morphological segmentation). For each split point, my model assigns a probability. The word is to be split at the points where the probabilities are high. For example, in the word "walkings", there are 8 possible split points that each has got a probability. The point after "s", and the point after "ing" are expected to be comparably higher than others.
To give an idea an array of logarithms of these probabilities could be:
1093180.2921060047 -1099512.0227943386 -1095977.4780250955 **** -1101739.5058371008 -1103636.1269468896 -1103636.1269468896 -1103636.1269468896 -1103636.1269468896 -1103636.1269468896 - 1096910.8541777392 **** -1103636.1269468896 -1103636.1269468896
Here the split points that need to be found are marked with ****.
Thanks a lot in advance.
After adjusting the values, now I have a large set of values from which I need to find the local maxima. Do I need to do any curve fitting for that. I don't know what shape the curve has got. I have around 100.000 values which are positive values. And just I want to find the local maxima values.
Any idea is highly appreciated!