- What we need to install weka on mac how to#
- What we need to install weka on mac code#
- What we need to install weka on mac download#
Import the myrunsdatacollector.zip into ADT/Eclipse and load it on to your phone. The training phase boils down to the following steps at a high level: What we need to install weka on mac code#
The training phase is illustrated in the figure below - don't panic: we do not expect you to write low-level signal processing functions such as compute the FFT - we give out code to do that.
What we need to install weka on mac how to#
I will show how to collect activity data using MyRuns Data Collector and teach you how to play with Weka GUI to train your own classifier. In what follows, we only discuss the training phase where we collect data and create a classification model.
calling the WekaClassifier inputting the feature vector - this is called the classification phase and produces an inference (e.g. adding the maximum value of the magnitude across all 64 individual magnitudes to the feature vector and. segmenting features into batches of 64 features in a buffer - this is called the feature vector. computing the FFT coefficient of the magnitude - this is called a feature. 
computing the magnitude from a single x, y, z reading. reading the x, y, z sensor data from the SensorManager. Other parts of the pipeline are as follows (include the WekaClassifier): Second, the classification or inference phase where we embed the WekaClassifier produced by WEKA into our MyRuns5 project in a file called WekaClassifier.java - this forms one component of the classification pipeline that runs as part of your application. Technically, this technique is called "supervised learning" in machine learning (ML) parlance. First, the training phase where we collect data using the MyRuns data collector (which you are given) and label the data (e.g., walking) and then feed the resulting sensor data into WEKA(Waikato Environment for Knowledge Analysis - a very cool machine learning tool) which, in turn produces a classifier (called the WekaClassifier java class in our MyRuns5) that we embedded in our MyRuns5 to form a component in what is called the activity recognition "classification pipeline. Libraries and the header files and re-run R CMD INSTALL.In this lecture, we will discuss the training phase of activity recognition the complete machine learning task of building a classification system that can automatically infer your activity (e.g., standing, walking, running) breaks down into two sequential phases: Manually specify the location of the MySQL Referenced from: /usr/local/Cellar/r/2.15.2/R.framework/Versions/2.15/Resources/library/RMySQL/libs/RMySQL.soĬould not find the MySQL installation include and/or libraryĭirectories. 
onLoad failed in loadNamespace() for ‘RMySQL’, details:Ĭall: dyn.load(file, DLLpath = DLLpath, …)Įrror: unable to load shared object ‘/usr/local/Cellar/r/2.15.2/R.framework/Versions/2.15/Resources/library/RMySQL/libs/RMySQL.so’:ĭlopen(/usr/local/Cellar/r/2.15.2/R.framework/Versions/2.15/Resources/library/RMySQL/libs/RMySQL.so, 6): Library not loaded: libmysqlclient.18.dylib ** testing if installed package can be loadedĮrror. These steps will get you over these ugly errors: library(RMySQL) should know work in the R interactive shell. This is documented as one of the options in the installation guide.ħ. In terminal, use the following command to install RMySQL. R CMD INSTALL –configure-args=’–with-mysql-dir=MYSQL_HOME –with-mysql-inc=MYSQL_HOME/include –with-mysql-lib=MYSQL_HOME/lib’ RMYSQL_PATH. Before installing RMySQL, we need to place libmysqlclient.18.dylib in a place where RMySQL can find it. sudo ln -s MYSQL_HOME/lib/libmysqlclient.18.dylib /usr/lib/libmysqlclient.18.dylib.Ħ. We’ll refer to the path of that RMySQL_ as RMYSQL_PATH.ĥ.
What we need to install weka on mac download#
Download RMySQL package source from CRAN. It should contain directories such as bin, lib, and include.Ĥ. Uncompress somewhere which we’ll now refer to as MYSQL_HOME.
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