Write down major role of data reduction in machine learning process by using suitable example data

Data reduction:

Data reduction in machine learning is a technique which reduce data which is written in huge volume or data which in huge size will be in less volume but in this process, the integrity of data will be insure. Data is it in not lost the actual meaning.
There are so many techniques use I it to reduce in data volume and kept its accuracy and integrity. These techniques are as follows:

Major role of data reduction in machine learning:

Data reductions have so many major roles in machine learning few of them are as follows:

·         When data is in large form there is so many difficulties to apply different technique on it, so when we distributes it so it will quite easy to apply techniques on it.

·         Sometimes we collect data for different surveys for different sites and different areas and data would b very in all cases.in this case difficult to deal with is for this purpose we use data reduction techniques.

·         Data reduction techniques used to reduce the complex queries and complex data set into small and well manners which is very easy to do analysis on it. By maintain its integrity.

·         In this technique we just convert the large size data into smaller size it does not mean data before alter and after alter will be change, data will be same but it will be classify or clustering according to the nature.

·         Sometimes data is in the form of different objects and different objects have different values and attributes so we apply techniques according to it like clustering sampling or calcification etc.

·         Before final output raw data should be converted via using different algorithm into different forms to extract he exact values.

Example of data reduction in machine learning process:

In elections of any country there are lots of raw data, which is in the form of figures numbers and images etc., data is from differs cities from different people of different age, without applying reduction techniques it is very difficult to do analysis and find few queries like from which city how many male female cast vote to which leader and what age of people cast votes to which leader, which city have more votes from female, male and youngsters etc. so for this purpose we need to apply all these techniques on it like classification of all data according to the figures and these values to conduct these survey for any elections. After this classification we will be able to answer all the questions easily.