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WhatsApp: +86 182217550734. Machine learning and our focus Like human learning from past experiences. A computer does not have "experiences". A computer system learns from data, which represent some "past experiences" of an application domain. Our focus: learn a target function that can be used to predict the values of a discrete class attribute, e.g., approve or not-approved, and high …
WhatsApp: +86 182217550737. What is SAP Plant Maintenance • Plant Maintenance is a function or an essential support system in an industrial process.This system helps and keep all the machinery and infrastructure into prime condition or ideal in terms of quality and operational. SAP Plant Maintenance comprises the following activities: • Inspection Determining the actual condition …
WhatsApp: +86 182217550737. DATA MINING ILOs Upon completion of the course, the students will: be able to handle a problem in a wide range of business cases and scientific disciplines, assess whether and how the problem is solvable by data mining, obtain and process the necessary data, perform exploratory analysis, create visualizations, full report, and executive summary for decision …
WhatsApp: +86 182217550732. What's it all about? Data vs information Data mining and machine learning Structural descriptions Rules: classification and association Decision trees Datasets Weather, contact lens, CPU performance, labor negotiation data, soybean classification Fielded applications Loan applications, screening images, load forecasting, machine fault diagnosis, …
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WhatsApp: +86 18221755073A salt pan worker in a salt evaporation pond in Tamil Nadu, India Subsurface Mining: Room-and-Pillar Mining "Rooms" are cut into seams of coal (or salt or iron) Pillars of ore are left standing to support the ceiling When all possible ore is extracted from the rooms – often the pillars are then removed and the land above collapses ...
WhatsApp: +86 1822175507313. GOAL & it's Keywords • The goal of the SVM algorithm is to create the best line or decision boundary that can segregate n-dimensional space into classes so that we can easily put the new data point in the correct category in the future. This best decision boundary is called a hyperplane. • Support vectors are data points that are closer to the hyperplane and …
WhatsApp: +86 1822175507311. Ensemble Learning Techniques/Methods Bootstrap Aggregating / Bagging Again at first step multiple machine learning models are generated. These models are generated using the same machine learning algorithm with n random observations of m sub-samples of the original dataset using bootstrap sampling method. The second step is aggregating the result …
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WhatsApp: +86 1822175507323. Cons : It doesn't perform well, when we have large data set because the required training time is higher It also doesn't perform very well, when the data set has more noise i.e. target classes are overlapping SVM doesn't directly provide probability estimates, these are calculated using an expensive five-fold cross-validation.
WhatsApp: +86 182217550736. Hierarchical Clustering Algorithms • Two main types of hierarchical clustering – Agglomerative: • Start with the points as individual clusters • At each step, merge the closest pair of clusters until only one cluster (or k clusters) left – Divisive: • Start with one, all-inclusive cluster • At each step, split a cluster until each cluster contains a point (or there are k ...
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WhatsApp: +86 182217550733. The name machine learning was coined in 1959 by Arthur Tom M. Mitchell provided a widely quoted, more formal definition of the algorithms studied in the machine learning field: A computer program is said to …
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