diff --git a/lib/node_modules/@stdlib/ml/base/sgd/params/factory/README.md b/lib/node_modules/@stdlib/ml/base/sgd/params/factory/README.md
index 7b08aa6c1c29..66fdc93668b5 100644
--- a/lib/node_modules/@stdlib/ml/base/sgd/params/factory/README.md
+++ b/lib/node_modules/@stdlib/ml/base/sgd/params/factory/README.md
@@ -149,9 +149,7 @@ var params = new Params({
     'fitIntercept': true
 });
 
-var str = params.toString({
-    'format': 'linear'
-});
+var str = params.toString();
 console.log( str );
 
 Params = paramsFactory( 'float32' );
@@ -167,9 +165,7 @@ params = new Params({
     'fitIntercept': true
 });
 
-str = params.toString({
-    'format': 'linear'
-});
+str = params.toString();
 console.log( str );
 ```
 
diff --git a/lib/node_modules/@stdlib/ml/base/sgd/params/factory/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd/params/factory/examples/index.js
index de75bd30925c..b989b4e9a282 100644
--- a/lib/node_modules/@stdlib/ml/base/sgd/params/factory/examples/index.js
+++ b/lib/node_modules/@stdlib/ml/base/sgd/params/factory/examples/index.js
@@ -35,9 +35,7 @@ var params = new Params({
 	'fitIntercept': true
 });
 
-var str = params.toString({
-	'format': 'linear'
-});
+var str = params.toString();
 console.log( str );
 
 Params = paramsFactory( 'float32' );
@@ -53,7 +51,5 @@ params = new Params({
 	'fitIntercept': true
 });
 
-str = params.toString({
-	'format': 'linear'
-});
+str = params.toString();
 console.log( str );
diff --git a/lib/node_modules/@stdlib/ml/base/sgd/params/factory/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd/params/factory/lib/main.js
index 04c33880526c..85cde92cb143 100644
--- a/lib/node_modules/@stdlib/ml/base/sgd/params/factory/lib/main.js
+++ b/lib/node_modules/@stdlib/ml/base/sgd/params/factory/lib/main.js
@@ -72,8 +72,8 @@ var isDataType = contains( DTYPES );
 * var params = new Params();
 * // returns <Params>
 *
-* params.penaltyParams = new Float32Array( [ 2.5, 0.0 ] );
-* params.learningRateParams = new Float32Array( [ 0.01, 0.0 ] );
+* params.penaltyParams = new Float64Array( [ 2.5, 0.0 ] );
+* params.learningRateParams = new Float64Array( [ 0.01, 0.0 ] );
 * params.lossFunctionParams = new Float64Array( [ 0.0 ] );
 * params.intercept = 0.0;
 * params.maxIter = 500;