So first we find what are the problems occurring in our data, ABT (Analyze Base Table) in our data we can view from the excel file, and use some excel filter menus to find details of the datas. If data is noisy we can’t do further steps for analysis. Preprocessor – Preprocessor is used to clean the noisy data. we must care about that noise, for example, null values, Duplicate values, empty space, irrelevant fields like that. same thing the data also Usually this data has lots of noise.
The above picture help us to understand more about weka tool Raw Dataĭid you see the field of paddy it represents raw data, the paddy needs to dry, and then boiled and then cleaned that cover then only we can get rice, and on the other side you can see the bowl of rice represents the cleaned data, yes this forms only we can get food. Weka supports several standard data mining tasks, more specifically, data pre-processing, clustering, classification, regressing, visualization and feature selection. It contains a Collection of visualization tools and algorithms for data analysis and predictive modeling coupled with graphical user interface. It is a suite of machine learning software developed at the University of Waikato, New Zealand. Weka – Waikato Environment for Knowledge Analysis (Weka) In this blog, we are going to see one important data mining tool.
Data handling is an important role of every organization. Properly collected is without spelling mistakes, without missing values, or without duplicate values. If we collect our data properly, we can use that data to analyse our business understanding. You can think about how it is possible, one product seller wants to sell their product in a place, but he doesn’t know anything about that place and people, so they want to study that place and get a decision to sell their products. We don’t know about the importance of our information, but that data is important to some other people to develop their business. Nowadays that data is maintained through the computer because our life is embedded with data, for example, our name is a kind of data and our living place, date of birth, in our government provides aadhar number that is also kind of data, in schools, students particulars, in supermarkets customer details, product details, customer purchase details, in bank account holder details, credit card holder details etc…. But it needs lots of paperwork, it is time-consuming. That record helped them to analyse the data to make future decisions. In previous days peoples maintained their business details manually, handwritten data records were very important those days. One man, sitting in his office, using computer for mining bitcoin.īefore we move onto the Weka tool, we need some ideas about data.
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