@keyword_only
@since('3.0.0')
def setParams(self, featuresCol='features', labelCol='label', predictionCol='prediction', factorSize=8, fitIntercept=True, fitLinear=True, regParam=0.0, miniBatchFraction=1.0, initStd=0.01, maxIter=100, stepSize=1.0, tol=1e-06, solver='adamW', seed=None):
    '\n        setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction",                   factorSize=8, fitIntercept=True, fitLinear=True, regParam=0.0,                   miniBatchFraction=1.0, initStd=0.01, maxIter=100, stepSize=1.0,                   tol=1e-6, solver="adamW", seed=None)\n        Sets Params for FMRegressor.\n        '
    kwargs = self._input_kwargs
    return self._set(**kwargs)
setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction",                   factorSize=8, fitIntercept=True, fitLinear=True, regParam=0.0,                   miniBatchFraction=1.0, initStd=0.01, maxIter=100, stepSize=1.0,                   tol=1e-6, solver="adamW", seed=None)
Sets Params for FMRegressor.
@keyword_only
@since('3.0.0')
def setParams(self, featuresCol='features', labelCol='label', predictionCol='prediction', factorSize=8, fitIntercept=True, fitLinear=True, regParam=0.0, miniBatchFraction=1.0, initStd=0.01, maxIter=100, stepSize=1.0, tol=1e-06, solver='adamW', seed=None):
    '\n        setParams(self, featuresCol="features", labelCol="label", predictionCol="prediction",                   factorSize=8, fitIntercept=True, fitLinear=True, regParam=0.0,                   miniBatchFraction=1.0, initStd=0.01, maxIter=100, stepSize=1.0,                   tol=1e-6, solver="adamW", seed=None)\n        Sets Params for FMRegressor.\n        '
    kwargs = self._input_kwargs
    return self._set(**kwargs)