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    5,477 matlab svm toolbox regression trabalhos encontrados, preços em USD

    Na atualidade, está a emergir um novo paradig...desenvolvido visa definir um modo de interação baseado no desenho de letras no ar, e realizar a interpretação dos símbolos desenhados, usando os reconhecedores de padrões KDA, SVM e $N. [login to view URL]

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    ...entry. You must have experience with SPSS and the following statistical tests: raw frequencies and adjusted odds ratios (OR) with 99% confidence intervals (CI), logistic regression analysis WHILE accounting/adjusting for confounding variables. The person I select to help me with this must be able to discuss the study design and understand the clinical

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    QA Manual Tester 5 dias left

    ...least 2 years experience doing QA in software development projects (web and mobile) -Strong knowledge in software QA methodologies, tools and processes (functional, smoke, regression) -Experience in agile methodology -Excellent communication and documentation skills -Can write test plans -Can work under minimal supervision and can attend daily scrum -Experience

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    ...files are getting too big and calculations are too hard for this program and my computer. I think that Matlab/R/Python is much faster in calculating that is why I approached you. I have a panel dataset and I want to use time fixed effects regression to estimate a model and forecast values with the fitted model. My panel data is unbalanced and has 40

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    I need you to fix the weak accuracy problem of my current network anomaly detection system which uses machine learning algorithm (SVM) to detect network packets with anomalies. Good knowledge of network programming and machine learning are necessary.

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    12 ofertas

    Basic knowledge on BottomUp Binary Hierarchical Classifier, Pair Wise Classifier, SVM etc.

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    Multiple regression analysis to test the hypotheses (Cohen et al. 2003). To avoid problems with multicollinearity, we mean-centered the exogenous variables, as Cohen and colleagues (2003) recommend. The variance inflation actors indicate that multicollinearity is not a threat to the conclusions of the study. To test for the relative magnitude of the

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    ...I have an urgent project ! As more flexible and fas you are, the better your chances. WHAT YOU SHOULD DO A simple data analysis needs to be done with econometric software (Matlab, Stata or R) (Please see the attachments: DataSet and detailed project and work description is attached) Model: One dependent variable (3), two independent variables (1 and

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    ...and Derivative commodities in Agriculture space. The model should cover entire flow of Instrument valuation, various Hedge Effectiveness testing - Dollar Offset, Linear Regression and generation of A/C Entries based upon Cash Flow and Fair Value Hedge. The A/C Entries should include bucketing of OCI & PnL accounts. More information can be discussed

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    Trophy icon Unicorns and Rainbows 1 dia left

    Hi All, I need 2 images for some slides. The topic is about UI regression and how something great can become something with the same elements, but now be not so great. I would like both images to be of a super sonic rainbow powered unicorn (or alicorn/pegacorn). The unicorn in both images needs to be obviously the same animal. Impressions

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    ...to implied by the betting market goal and win supremacy. Then model should look back over the season's games for each football league and use (probably?) standard linear regression techniques to come up with a set of rankings that are most consistent with the derived before goals and supremacy values for those games Here's a good explanation of what

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    ...and E are unnecessary and extraneous, and I don't wish to have them in the final Python script, unless they are necessary. Recreation of pandas now-deprecated rolling() regression functionality for multivariate linear regressions. I believe this has been deprecated, but it appears still listed in the pandas documentation. If it is still functional

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    We need a Python script to take in any given dataset (meaning either a regression task or a machine learning task) and select features according to four feature selections algorithms which will be provided. We are expecting the following: df_raw df_one df_two df_three df_four where df_raw is what we provide and df_one...df_four are the dataframes you

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    ...and E are unnecessary and extraneous, and I don't wish to have them in the final Python script, unless they are necessary. Recreation of pandas now-deprecated rolling() regression functionality for multivariate linear regressions. I believe this has been deprecated, but it appears still listed in the pandas documentation. If it is still functional

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    12 ofertas
    Machine Learning Encerrado left

    Looking for Python programmer for Machine learning implementation. Minimum Experience 6 months. Simple implementation of Basic Algorithms. Like SVM, Linera Regression, Random Forest Regression

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    Business Problem - Company collected data from 5000 customers. The objective of this case study is to understand what's driving the total spend of credit card(Primary Card + Secondary card) Prioritize the drivers based on the importance.

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    generate algorithm using feature selection ReliefF and classifiers...with MLP , SVM

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    Company collected data from 5000 customers. The objective of this case study is to understand what's driving the total spend of credit card(Primary Card + Secondary card) Prioritize the drivers based on the importance. There are several KPIs driving the expenditure like age group, income, gender, cardtyoe

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    need some modification of attached standard tflearn code to 1. target variable is column 1 2. 17 variables to predict column 1 3. divide csv data into train and test (80/20) 4. stop model when acceptable R2 reached 5. prediction of column 1 from other 17 variables

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