When we have a dataset on hand, it is often of our interest to run a quick analysis and get some insights. The analysis usually includes making predictions of a new dataset, grouping records, identifying important features, and optimization. We can achieve these goals by building a machine learning model and use the trained model…
NOTE: Robustness reported in this article is being revised with corrections in derivative calculations. Updated results will be published shortly from these corrections. Introduction A natural approach of understanding an unknown model is to get some sample points from the model and use these points to build a response surface model (RSM) to represent the…
Similar to the dataset_simulated_annealing_optimizer worker, which takes a dataset as input, we can consider the curve_simulated_annealing_optimizer worker. It takes a curve as input and returns the optimal y value of the curve as output. A curve can be considered as a dataset with two columns with each representing one coordinate of the points on a…
Many of us would agree that calendars play an important role in our day-to-day life aiding in tracking events, staying on top of task completion, etc. Calendar in d3VIEW helps keep track of Simulations and Physical tests records created by users in an organized manner. How to access Calendar: All the simulation and physical test…
Optimization Decisions are made based on preferences. Either it is to minimize the monthly expense for a person living with a tight budget or to maximize the revenue of a restaurant for a business owner, we need to consider our preference or criteria (minimize or maximize) to form a solution. This process is called optimization…
In the previous post, we have discussed about how interpolation works in general and reviewed a few commonly used interpolation methods. All these methods only consider the adjacent a few points. This works fine most of the time. However, in reality, data points further away from the interpolation point may also have some impact on…
Machine learning is a data analysis technique that builds a model with the data and uses the model to predict. It learns from the data, identifies patterns and produces reliable predictions that help with decision making. As modern computational techniques advance, machine learning becomes more and more popular. There are two major groups of learning…
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