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it("should make test number 83", function () {
// import analytics module
var analytics = require('qminer').analytics;
// create a new OneVsAll object with the model analytics.SVC
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: { c: 10, maxTime: 12000 }, cats: 2 });
// set the parameters
var params = onevsall.setParams({ model: analytics.SVR, modelParam: { c: 12, maxTime: 10000}, cats: 3, verbose: true });
});
});
it("should make test number 84", function () {
// import modules
var analytics = require('qminer').analytics;
var la = require('qminer').la;
// create a new OneVsAll object with the model analytics.SVC
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: { c: 10, maxTime: 12000 }, cats: 2 });
// create the data (matrix and vector) used to fit the model
var matrix = new la.Matrix([[1, 2, 1, 1], [2, 1, -3, -4]]);
var vector = new la.Vector([0, 0, 1, 1]);
// fit the model
onevsall.fit(matrix, vector);
// create the vector for the decisionFunction
var test = new la.Vector([1, 2]);
// give the vector to the decision function
var prediction = onevsall.predict(test); // returns the vector of scores
});
});
it("should make test number 86", function () {
// import modules
var analytics = require('qminer').analytics;
var la = require('qminer').la;
// create a new OneVsAll object with the model analytics.SVC
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: { c: 10, maxTime: 12000 }, cats: 2 });
// create the data (matrix and vector) used to fit the model
var matrix = new la.Matrix([[1, 2, 1, 1], [2, 1, -3, -4]]);
var vector = new la.Vector([0, 0, 1, 1]);
// fit the model
onevsall.fit(matrix, vector);
});
});
it("should make test number 82", function () {
// import analytics module
var analytics = require('qminer').analytics;
// create a new OneVsAll object with the model analytics.SVC
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: { c: 10, maxTime: 12000 }, cats: 2 });
// get the parameters
// returns the JSon object
// { model: analytics.SVC, modelParam: { c: 10, maxTime: 12000 }, cats: 2, models: [] }
var params = onevsall.getParams();
});
});
it('should not throw an exception, dense vector', function () {
this.timeout(10000);
var json = { c: 10, maxTime: 12000 };
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: json, cats: 2 });
var matrix = new la.Matrix([[1, 2, 1, 1, -3, -4], [2, 1, -3, -4, 2, 2]]);
var vector = new la.Vector([0, 0, 1, 1, 1, 1]);
onevsall.fit(matrix, vector);
var test = new la.Vector([1, 2]);
assert.doesNotThrow(function () {
var prediction = onevsall.predict(test);
});
})
it('should return the index of the cluster, where it the most fit, dense vector', function () {
it('should throw an exception if no parameters are given', function () {
var json = { c: 10, maxTime: 12000 };
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: json, cats: 10 });
assert.throws(function () {
onevsall.setParams();
});
})
});
it('should set the parameters and override the old ones', function () {
var json = { c: 10, maxTime: 12000 };
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: json, cats: 10 });
var params = onevsall.getParams();
assert.equal(params.cats, 10);
assert.equal(params.modelParam.c, 10);
assert.equal(params.modelParam.maxTime, 12000);
assert.equal(params.models.length, 0);
assert.equal((new params.model(params.modelParam)).getParams().c, 10);
onevsall.setParams({ model: analytics.SVR, cats: 5 });
var params = onevsall.getParams();
assert.equal(params.cats, 5);
assert.equal(params.modelParam.c, 10);
assert.equal(params.modelParam.maxTime, 12000);
assert.equal(params.models.length, 0);
assert.equal((new params.model(params.modelParam)).getParams().c, 10);
})
it('should throw an exception if no parameters are given', function () {
it('should throw an exception if only the matrix is given', function () {
this.timeout(10000);
var json = { c: 10, maxTime: 12000 };
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: json, cats: 2 });
var matrix = new la.Matrix([[1, 2, 1, 1, -3, -4], [2, 1, -3, -4, 2, 2]]);
assert.throws(function () {
onevsall.fit(matrix);
});
})
});
it('should throw an exception if the number of rows are greater than the models', function () {
this.timeout(10000);
var json = { c: 10, maxTime: 12000 };
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: json, cats: 2 });
var matrix = new la.Matrix([[1, 2, 1, 1], [2, 1, -3, -4]]);
var vector = new la.Vector([0, 0, 1, 1]);
onevsall.fit(matrix, vector);
var test = new la.Matrix([[1, 1], [2, -3], [2, 3]]);
assert.throws(function () {
var decision = onevsall.decisionFunction(test);
});
})
it('should throw an exception if the number of rows are lesser than the models', function () {
it('should set the models, dense matrix', function () {
this.timeout(10000);
var json = { c: 10, maxTime: 12000 };
var onevsall = new analytics.OneVsAll({ model: analytics.SVC, modelParam: json, cats: 2 });
var matrix = new la.Matrix([[1, 2, 1, 1, -3, -4], [2, 1, -3, -4, 2, 2]]);
var vector = new la.Vector([0, 0, 1, 1, 1, 1]);
onevsall.fit(matrix, vector);
var param = onevsall.getParams();
assert.equal(param.models.length, 2);
})
it('should set the models, sparse matrix', function () {