The algorithm enables a “backward propagation” over the respective neurons to make them more appropriately perceptive for the problem at hand (the essential functionality of that particular neural network for the requisite problem-solving). Altair and RapidMiner share the same vision to make data analytics simple enough for all users, but scalable, governed, and safe enough for all enterprises. The data is run through a number of neurons over a number of different layers (to process different aspects of the data), with subsequent layers dependent on activations in the prior ones. There has to be a target variable that will be predicted. Nave Bayes, Decision Tree, Random Forest and Support. Decision Tree Algorithm: Percentage Accuracy. comparison of the various classification algorithms like K-nn. The data is in a basic spreadsheet and / or general dataframe structure, with variables in the column headers, row data as examples, and the information cells as numeric values (including for dummy and for categorical values). METHODOLOGY In this paper the RapidMiner Studio 68 was used to perform experiments by taking the past. Basically, variables as columnar data is fed into the ANN, and based on observed features, the artificial neural network will reduce the data to particular outcomes. The “neurons” are represented by the round nodes, and the “synaptic signals” are represented by the lines (paths for the synaptic signaling). Based on this basic approach, many types of ANNs have been created.
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